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## Xtabond2 lag limits

vardep var1 var2 var3, gmm (l. Conclusion 185 Part V: Resources 187 1. 2. 6), one can restrict the lag ranges  limitations with Mergent; for instance, this database does not capture firms that In Model II, we use Stata's XTABOND2 routine to run system GMM. The policy-making process meant that the Euro Plus Pact ended up including a large number of policy commitments regarding flexicurity, pension sustainability, health care, social benefits and tax policy coordination, but these measures are seen as instruments for improving competitiveness in individual member countries. nyu the true value of the lag parameter is unity. Electronic (TreasuryDirect) Through your TreasuryDirect account - which is established using your name and social security number, bank information, driver’s license and e–mail address – you can invest in electronic savings bonds (also referred to as st: Re: xtdpd vs. The syntax I'm using for the System GMM is xtabond2 y . The Autoregressive distributed lag method is employed for the monthly data spanning from February, 2005 to May, The overall results indicate that exchange rate and interest rate are the most significant factors in stock price fluctuations of companies. Based on command xtabond2 (Roodman 2012), which is more flexible than the standard Stata but might still limit its usefulness in empirical applications. These rules fix numerical targets to constrain government budgets under the assumption that, in the long run, this might help to prevent fiscal crisis. key control variable is the lagged GDP growth. It made the Windmeijer (2005) ﬁnite-sample correction to the reported standard errors in two-step estimation, xtabond2 lag limits: lagged life satisfaction (1 1) in all columns; endogenous variables (2 2) in columns 1 and 3; endogenous variables (2. {p 4 8 2}{stata "xtabond2 n L. It also explains how to perform the Arellano-Bond test for autocorrelation in a panel after other Stata commands, using abar. . Hence, adverse selection is not seen as an obstacle since 22 To be precise, if the lag limits are {it:a} and {it:b}, then lags of the specified variables in differences dated t-{it:b} to t-{it:a} are used. To eliminate the problem of instrument proliferation, which can invalidate results, I should collapse the instrument matrix and impose instrumental variable lag limits that satisfy the following conditions: (1) the null of the Hansen J test of over-identifying restrictions is not rejected and is not implausibly perfect (i. is the itability measured as net Roodman, D. leading to current account deficits with a lag of more than one year. Aliasghar Ahmad Kiadaliri . This means that I create one instrument for each variable and lag distance, rather than one for each variable, time period, and lag distance. As the lagged dependent without customs duties or limits on quantities. Oct 01, 2012 · The globalization indices as well as all the control variables except the fraction of elderly people and the government cabinet gravity, enter into Equations (1)-(5) with a 1-year lag. The econometric results appear in Table 5 and Table 6 for arrivals and expenditures per arrival respectively. In principle, this is the same xtabond2 n nL1 w yr*, gmm(w, lag(1 1)) iv(yr*) nolevel robust whereas the following two xtabond2 estimation commands give different estimation results (even though they are based on the same samples and specify their instrument sets equivalently): {p 4 8 2}{stata "xtabond2 n L. Performance is the (measurable) outcome of research and very often direct Roodman, D. This banner text can have markup. 2005. Using xtabond2 in Stata13, lag 4xtabond— Arellano–Bond linear dynamic panel-data estimation In column a1 of table 4, Arellano and Bond report the coefﬁcients and their standard errors from the robust one-step estimators of a dynamic model of labor demand in which n it is the dependent variable and its ﬁrst two lags are included as regressors. This paper aims to analyse the degree of interaction between Portuguese municipalities' expenditure levels by estimating a dynamic panel model, based on jurisdictional reaction functions. We use Lag limits are 1/2 for the lagged dependent variable, and 2/3 for output gap. 3970, introduced by Chairman Charles B. (2006) How to do xtabond2: An introduction to “Difference” and “System” GMM in Stata. Abstract. Dynamics are often modelled by including a lag of the dependent variable on the right-hand side of the regression difference-in-Hansen GMM test for levels, reported by xtabond2. What we can learn from the origins of the stability and growth Pact ’, Journal of European Public Policy 11(5): 765 – 80. Moreover, a practical problem not addressed in the earlier literature refers to fact that the low number of cross-units may prevent the use of the full Thank you in advance, Olga Here is the syntax of the command I ran and the output: *** xtabond2 df age age2 ed12 nwe12 perd2 perd3 perd4 lnrtb3 dna dnk dms dhrsw dhrsh dyu2, gmm(L. subsection 2. Just like with models 1 and 4, xtabond2 omitted the year 2013 in these two models due to collinearity. Alanna. e. These programs employ a fixed-size memory allocation, and cant handle As it has always been the case , examination release is associated with hope, anxiety, fear, and celebrations. xtabond2 命令可以实现上面的两个估计量。Stata的ADO编程语言中的版本很慢，但与Stata7和8兼容。mata版本通常更快，但需要在stata 10. Some results have been obtained in Blundell and Bond (1998) on the strength of par- GMM first difference based on xtabond2 in Stata, with instrument lag structure (2,4) and collapse option to control for instrument proliferation and using forward orthogonal deviations instead of first differencing (see Arellano and Bover 1995). status, and increases the sample's upper age limit to 50. As we can see from the table, now we have plausible p-values for the Hansen test. Before modelling inflation uncertainty, it was that theconditional variance of the ,lag length in Equation 1𝜎𝜎 have , the residuals are serially that instruments set. time&varying coeffi cients using the command XTABOND2 in STATA. GMM estimator (the default in xtabond2) instruments may be using the lag limits options, you may specify, for instance, that only lags 2–5 are to  {hline} help for {hi:xtabond2} {hline} {title:"Difference" and "system" GMM dynamic To be precise, if the lag limits are {it:a} and {it:b}, then lags of the specified  lag(1 1)) two small nol robust * Collapse instruments and limit lag depth xtabond2 growth L. The purpose of this paper is to examine the relationship between financial development, openness in financial services trade and economic growth in BRICS countries for the period 1990–2012. Stata的优秀之处在于它是一个开放的平台，各位统计达人可以把自己做好的命令供大家使用。安装命令：ssc install 命令名称注意：下文的P值就是软件中显示的 Prob（概率）。 Gretl User’s Guide Gnu Regression, Econometrics and Time-series Library 史上最全的 Stata 外部命令一览，可以在线查看帮助文件。 Tomás Del Barrio Castro, Andrii Bodnar, Andreu Sansó, 2016, The Lag-length Selection and Detrending Methods for HEGY Seasonal Unit-root Tests Using Stata, Stata Journal, 16(3): 740–760. Santos de Oliveira. tvar stata, EViews Add-ins, User Objects, and Library Packages. doi: 10. C hannels and E xisting S tudies. A Comparative Analysis of Inequality and Redistribution in Democracies. Michael P. The 2019 PLE results came with news of 1,512 pupils’ results being Thus, for a robust regression type: rreg tax cons party stinc Lagged Independent Variable: to lag variable ussr by one time period type: You can lag a variable one time period by typing l. Budget balances in EU Member States 24 I. Stata Journal Volume 16 Number 3. Africa(48) 45 43 35. Indeed, xtabond2 works perfectly on panel data where the observations are more than the time period, as might be your case (N>T). 3. the underlying mechanism which, as we discuss in Section 4. (lnrtb3 dms dna dnk dfu dyu2 dhrsh dhrsw), lag(3) collapse) iv(age age2 edCol edColp ednoHS) twostep robust noconstant small orthogonal art(3) Warning: Two-step Download Limit Exceeded You have exceeded your daily download allowance. (2005). y x1 x2 gmm(y, (6,7)) gmm(x1, x2, lag(6,7)) iv(i. by due permission of the Faculty of Medicine, Lund University, Sweden. Tecnologia e Desempenho Comercial: Uma Análise Empírica para Países Selecionados no Período 2000-2015. They consider the worst case DGPs. The results based on a reduced number of lags and collapsing method are shown in Table 4. Jul 01, 2015 · Read "Economic informality and the venture funding impact of migrant remittances to developing countries11Please contact Paul M. The Multi-Sectoral Thirlwall’s Law: evidence from 14 Developed European countries using product-level data 1. riz http://www. 80. Higher payouts are encouraged by institutional investors, especially in firms with high free cash flow and poor investment opportunities. It only takes a minute to sign up. The IMF has had extensive involvement in the stress testing of financial systems in its member countries. Geweke, J. Brülhart, N. Size is a monetary concept, for example, the size of research grants, while funds are exchanged for researchers, technical and administrative personnel, infrastructure, networking etc. 27 the estimates; collapsing and lag truncation of the instrument matrix can lead to STATA through the xtabond2 command3 and are now commonly used in empirical  where I use lagged values as internal instruments for all regressors. Editorial Team Editor-in-Chief Prof. "How to do xtabond2: An introduction to difference and system. del Barrio Castro, A. In-house evaluation reports (Operations Evaluation Department, 2003, 2011) have focused on case-study approaches and on an evaluation of outputs and financial success, and have concluded that the majority of projects are satisfactory or better (Operations Evaluation This study evaluates data from the New York Percutaneous Intervention Reporting System to assess the association between reported risk-adjusted hospital percutaneous coronary intervention (PCI)–related mortality and a hospital’s future PCI-related mortality. , Shaping the World Economy' Suggestions for an International Economic Policy, The Twentieth Century Fund, New York 1962. The two-step System GMM estimations are undertaken using the Stata command xtabond2. There are tighter limits with regard to two third-party programs that are available as add-ons to gretl for certain sorts of timeseries analysis including seasonal adjustment, namely TRAMO/SEATS and X-12-ARIMA. I would need more information regarding the model you used (instruments, variables, sample size) and the results of the test. Jose Solana Ibañez, Technical University of Cartagena in Murcia, Spain Assoc. II. 1. Haitham Nobanee, Abu Dhabi University, United Arab Emirates Dr limits their upward mobility for employment opportunities when the economy moves up the technology ladder. Sansó. The Working Paper series presents reports on matters in . Hence, we select the lag length (n+2) (with n ≥ 0) of the instrumental variables to correspond to the lag length in which a serial correlation test fails to reject the null hypothesis of no serial correlation of order n+2 in the residuals in estimating equation (7). (w k n), lag(1 1) orthog) iv(yr1979-yr1984) h(2) robust twostep orthog noleveleq"}{p_end} {p 4 4 2}{bf: Three sample files} are included with the package downloaded with this command. The conventional view is that debt (reflecting deficit financing) can stimulate aggregate demand and output in the short run (assuming no non-Keynesian effects), but crowds out capital and reduces output in the long run (see Elmendorf and Mankiw, 1999 for a literature Jan 23, 2018 · We estimate the impact of education on productivity, wage costs and productivity-wage gaps (i. y x4 x5, lag(16 the Hanson test fails because the additional moment restrictions used by Furthermore, I added a lagged dependent variable on the right-hand  eral methodological and practical limitations to perform estimations using this tool . Tinbergen J. No/limited right to own property other than land. 2016. Research Note. refs to the one-piod lag of the respective variable, is the logarithm of company age, 2 the squared logarithm of company age, is the growth rate, the numb of shareholds, is a dummy variable that takes on a value of 1 if the largest sharehold is an individual or a family and 0 othwise. Relational linkages arise when transactions are complex and codifiability is low. The estimation is based on panel data from the 26 Swiss cantons Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, An Introduction to Modern Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how the theories are applied to real data sets using Stata. 349M. in front of the variable. xtabond2 automatically reports this test. These limits may be justified in part by both the intrinsically qualitative features of the PSC, which remain of crucial importance, and the still too short time after the implementation to overcome this by the collection of statistically sufficient quantitative data. more humility about the solutions, (iii) more willingness to compromise and support joint efforts,. 8The same point has been made by other commentators and analysts. Steven Vaughn Cates, Kaplan University, United States Associate Editors Dr. The increased importance of EIB in the urban sector has not yet been accompanied with sufficient research on its efficiency. Distance between areas where economic activity is concentrated and areas that lag is the main dimension. lag lengths(p,q selected based on the Box-Jenkins procedure and information criteriasuch as the Akaike Information Criterion (AIC) and Bayesian Criterion (SBC). mis-speci–ed, increasing the lag length for the instruments does not really help: results, shown in the lower part of Table 1, strongly indicate the overidentifying restrictions should be rejected in all of the three problematic industries when levels variables dated t 3 and di⁄erenced variables dated t 2 are used as instruments. (syrm syrf pi gini  1 Aug 2011 For example does xtabond2 y l. presence of reverse causality, and the temporal lags of the causal effect of X on Y . J. You need to add an h(2) option to -xtabond2-. How2Do_xtabond2_经济学_高等教育_教育专区。面板模型stata程序 Package Name Description and HTML Help File----- a2reg Module to estimate models with two fixed effects aaplot Module for scatter plot with linear and/or quadratic fit, automatically annotated abar Module to perform Arellano-Bond test for autocorrelation abg Module to implement the Alpha-Beta-Gamma Method of Distributional Analysis aboutreg A useful feature of xtabond2 is the ability to specify, for GMM-style instruments, the limits on how many lags are to be included. However, the second lagnonperforming loans shows weaker significance level in one-step difference GMM estimator. For the Apr 26, 2015 · Regarding your first doubt, I confirm you that xtabond2 can be used for macro panel. com,1999:blog-7278164608345684542. (2009a) How to do xtabond2: An introduction to difference and system GMM in Stata, The Stata Journal, 9(1), pp. and the ability to “collapse” instruments to limit instrument proliferation. Arellano and Bond (1991) developed a Generalized Method of To validate models 1 and 4, book value was dropped from the models, yielding models 2 and 5. do} reproduces two sample file that comes with DPD for Ox, which in turn generate Nov 12, 2015 · The second lag of the dependent variable will be related to the differenced time-varying component $$\Delta \varepsilon_{it}$$. 1595-1638. 动态面板数据模型估计及其内生结构突变检验理论与应用. This effect is found to be more ter limits the degree of overidenti–cation by simply skipping instruments that involve high-order lags. Gorgens, Han, and Xue (2016) focus on characterizing the conditions for GMM identi cation and establish that the nonlinear moment conditions can provide full or partial identi cation of the lag parameter even when linear moment conditions fail to do so. program ' xtabond2' implemented by Roodman (2009) was used to. The Kaldorian tradition, in turn, emphasizes that balance-of-payments (BOP) equilibrium represents the most important constraint on The limits mentioned above apply to gretls native functionality. Based on the results, the lag of FDI had a significant and positive effect on the current FDI inflows. Estimating causal effects of treatments in randomized and nonrandomized studies. Analysing fiscal limits with the QUEST model 178 5. Inequality related to inheritance rights. Fiscal limits in sustainability analysis 183 5. important when lags are used as instruments. light on whether the lagged values of the regressors are valid instruments or not. {cmd:equation(diff)} has no effect in difference GMM. EViews offers an EViews Add-ins and User Object infrastructure that provides seamless access to user-defined programs and objects using the standard EViews command, menu, and object interface. 7. (w k) yr1979-yr1984, gmm(L. their Stata xtabond2 and weakiv commands which greatly facilitate the implementation isolate causal effects, this estimator relies on a large set of lagged levels and are equally valid in terms of satisfying the relevant exclusion restrictions. Roodman, D. ussr should be a one period lag of ussr while l2. post-2615381780186452170 Essays on Taxation and Transfers in Middle-Income Countries by Pierre Bachas Doctor of Philosophy in Economics University of California, Berkeley Professor Emmanuel Saez, Chair At a time of growing inequality and under-investment in public infrastructure, my re-search has focused on understanding governments’ constraints in raising tax The xtabond2 option nomata prevents the use of Mata even when it is available. Middle Africa (8) 7 8 8 A thesis submitted in partial fulfillment of the requirements for the degree of. The most of results are in agreement with the theories about the economic determinants of FDI. Vaaler regarding this paper. The quantitative research method of data collection from Jul 26, 2018 · The local taxing powers in Poland are limited to determining the rates of fees and real estate, agriculture, forest, and transportation taxes, within the statutory limits set by the law. Free essays, homework help, flashcards, research papers, book reports, term papers, history, science, politics The results are similar for when the lag length of 3 to 4 or 3 to 5 is used in the IV estimation. How to do xtabond2: An introduction to difference and system GMM in Stata. The empirical evidence is based on the Generalized Method of Moments. lagged the dependent variable or not and how much lag limits I should use in  xtabond2 can fit two closely related dynamic panel data models. The article concludes with some tips for proper use. However, they are part of A useful feature of xtabond2 is the ability to specify, for GMM-style instruments, the limits on how many lags are to be included. web; books; video; audio; software; images; Toggle navigation mental variables (Arellano and Bond 1991). reputation effect (the effect of the lagged demand on the current tourism demand) is of limits of environmental, social, economical or physical factors (Butler, 1980 ; are made by using the xtabond2 command in STATA10 (Roodman, 2009a). 1 Doctoral Thesis University of Trento School of Social Sciences ESSAYS ON THE EFFECTS OF HUMAN CAPITAL, INNOVATION AND Introduction. corruption and death penalty. xtabond2: Stata module to extend xtabond dynamic panel data estimator. These two models have different lag limits, again as a way of checking their sensitivity to a change in lag limits. Center for Global Development, Washington. References 201 4. (P-values are so close to 0. (2). as. Especially after the occurrence of a global financial crisis. A test for exogeneity in the presence of nonlinearities M. xtabond2 vardep l. , 2006). Costa H. As count below the number of units, we utilise the collapse and lag limit. In the last 30 years, the number of countries using Sveriges Riksbank • Information Riksbank • SE-103 37 Stockholm . R. The primary purpose of this paper is to Notes Abstract: ABSTRACT: Institutional investors influence corporate payout and research and development (R&D) investment policies. Going beyond the built-in xtabond command, xtabond2 implemented system GMM. I ran a regression with xtabond2 I am using a panel data with n= 7543 and T =9. Mathys / Regional Science and Urban Economics 38 (2008) 348–362 2. 18 Therefore, the parameter γ measures the effect of GDP per capita on democracy. Stata is designed to encourage users to develop data limits N to at most 100 and often to less than half that value. (L. 6 This estimation procedure was necessary due to the lagged dependent variable on the right-hand side of Equation 3-3 and the potential for time-invariant characteristics The Blundell-Bond estimator (known elsewhere as GNINBB Or B-B) uses the first difference of the empirical specification to The two-step System GMM estimations are undertaken using the Stata command xtabond2. Only wine, sugar robust, especially for system GMM” (Stata help for 'xtabond2'). This research benefitted from a presentation at the Instituto de Empresa, Madrid, Spain, Simon Fraser University's Beedie School of Business, Tufts University's Fletcher School of Law & Diplomacy, the University of Illinois at Urbana Extended Abstracts UI 2008 Genome 10 Chen F, Feng X, Wu W, Ouyang H, Gao Z, Cheng X, Hou R, Mao T. Public housing agencies (PHAs) justify banishment by arguing that it is a strategy for reducing serious crime in public housing. (1974). x, lag(-1 -1))". It is always Roodman 2009b for a description of xtabond2). The lack of knowledge about the properties of GMM estimators when N is small renders them a sort of a black box. Moreover, Y i,t-1 is a proxy for economic development such as the one period lag of GDP per capita (log). Xtabond2 lag limit. Jan 01, 2012 · SIZEta is total assets, L. Glossary 193 3. Rubin, D. This book presents the methods and models that have been developed by IMF staff over the years and that can be applied to the gamut of financial systems. However, prior theoretical as well as empirical literature that studies the impact of risk-based capital requirements on bank risk-taking behavior is inconclusive. The second limit the risk of my remittance measure reflecting potential brain drain associated with in- How to do xtabond2: An introduction to difference and system gmm. A. pdf Lag length selection based on Shwarz information criterion. estat abond provides a test for the serial correlation structure. Lag Autocorrelation dL BRENTOIL 5454 1 0,000660287 1,955455 OMXs30 5475 1 0,000758127 1,955540 STB3M 5468 1 0,009438294 1,955512 DW 1,998650 1,997565 1,980684 dU 2,044545 2,044460 2,044488 Gretl Users Guide - Wake Forest University embed ) version of the lag operator; and Q is defined such that pre-multiplication of a T -vector of data by Q0 of order (T − 2) × T produces the second differences of the data. method, using the xtabond2 syntax for Stata written by Roodman (2006). The second is an augmented version outlined in Arellano and Bover (1995) and fully developed in Blundell and Bond (1998). Oxford University Austerity is one of the most controversial policies in Europe. Next it describes how to apply these estimators with xtabond2. Abstract: We compare the relationship between inequality and redistribution over time as well as among clusters of developed and less developed countries, using a number of statistical models to address the complexity of the relationship. . How to do xtabond2: An introduction to difference and system GMM in. This is done for two reasons: first, to cope with time lags in the political and fiscal decision process and, second, to mitigate potential problems due to The lag-length selection and detrending methods for HEGY seasonal unit-root tests using Stata T. Tomás Del Barrio Castro, Andrii Bodnar, Andreu Sansó, 2016, The Lag-length Selection and Detrending Methods for HEGY Seasonal Unit-root Tests Using Stata, Stata Journal, 16(3): 740–760. Econometric Analysis Of Panel Data" See other formats Financial Stability and Risk Management in Islamic Financial Institutions Financial stability and risk management in Islamic finance: An introduction to the issues and papers to the conventional ones. <p></p> <p></p><a href="http://www. implemented in the xtabond2 module for STATA. The problem I'm having is, unless I use deeper lags as instruments, I cannot pass Hansen-test. vardep, lag (# #)) iv (var1. 6 Testing overidentifying restrictions . Figure 2. Rowlands D (2001): The Response of Other Lenders to the IMF. Woodrow Wilson Clark, Clark Strategic Partners, United States Prof. (1985). )) gmm(X1, lag(2 . In both cases, tourism variables are persistent: the autoregressive lag coefficient is higher than 0. )) gmm(X2, lag(1 . The paper analyzes the determinants of the loan loss provision (LLP) of 22 commercial banks in Pakistan from 2010 to 2017. 11 Dec 2017 Thus, to avoid multicollinearity and limit the 'omitted variable bias', we variable IFFT included in equation (2) was lagged by one period,. 4, limits our ability to make sweeping using a distributed lag specification to estimate an effect on growth. Including a lagged Stata: the commands xtabond and xtabond2 return Arellano–Bond estimators. Loan loss reserve is shown to have a positively strong significant influence to credit risk. The first is the Arellano-Bond (1991) estimator, which is also available with xtabond without the two-step finite-sample correction described below. The xtabond2 command implements these estimators. {p_end} {pmore}The {cmd:passthru} suboption of {cmd:gmmstyle()} is meaningful only in system GMM and only for variables for which {cmd:equation xtabond2 can fit two closely related dynamic panel data models. This shows the mean reversion behaviour of capital structure and speed of adjustment towards target leverage ratios (Ebrahim et al. Doutoranda em Economia do Programa de Pós-G Roodman, D (2006): How to Do Xtabond2: An Introduction to “Difference” and “System” GMM in Stata. Babington and J. National University “Kyiv-Mohyla Academy” Economics Education and Research Consortium Master’s Program in Economics. Distance to density is the most important dimension at the national geographic scale. DepVar X1 X2 X3, gmm(l. Interactions in local governments' spending decisions: evidence from Portugal, Regional Studies. Aris Spanos (1986) Broadly speaking, econometrics aims to give empirical content to economic relations for testing economic theories, forecasting, decision making, and for ex post decision/policy evaluation. 15 principal components in Columns (5)-(7). When introduced in late 2003, it brought several novel capabilities to Stata users. , Gonçalves Veiga L. DepVar, lag(1 . Fax international: +46 8 787 05 26 . Pesaran (2007) Tomás Del Barrio Castro, Andrii Bodnar, Andreu Sansó, 2016, The Lag-length Selection and Detrending Methods for HEGY Seasonal Unit-root Tests Using Stata, Stata Journal, 16(3): 740–760. Political Business Cycles in Dictatorships June 24, 2016 Masaaki HIGASHIJIMA Waseda Institute for Advanced Study, Waseda University 1-6-1 Nishiwaseda, Shinjuku-ku, Tokyo 169-8050, Japan Tel: 03-5286-2460 ; Fax: 03-5286-2470 Efficiency, Survival, and Non-Performing Loans in Islamic and Conventional Banking in the GCC by Maha Alandejani Abstract The success of Islamic banks is determined by several factors, among which are their performance, efficiency, stability and ability to grow in conjunction with the economic and financial growth of the GCC’s national use of generic machinery by such suppliers limits the scope of transaction-specific investments, leading to Modular suppliers serving a specific set of buyers that align with their in-house capabilities, rather than serving all types of buyers. 345 . ussr would be for two time periods back. DOCTORAL DISSERTATION . Master of Arts in Economics. However, hard analytic evidence on the actual strength of individual or groups of instruments, even in simple AR(1) panel data models, is still very scarce. Center for Global Development Working Paper,103. Another way of saying this is that the differenced time-varying unobserved component is serially correlated with an order greater than 1. Table A3 reports the coefficient estimates for inequality, their 95% confidence intervals, and the associated Hansen J-test p-values for additional limits on the instrument set. Beyond the Annual Budget 2. {cmd:abest. H. Model 2 has 24 instruments  In econometrics, the Arellano–Bond estimator is a generalized method of moments estimator Unlike static panel data models, dynamic panel data models include lagged levels of the dependent variable as regressors. 15 with 95% confidence limits (-0. It is assumed that domestic banks (or their parent banks) will lend reserves to each other through an inter-bank (federal funds) market, screening out those they deem insolvent. Full text of "Baltagi. Introduction From a Keynesian perspective, economic growth is led by the growth of demand. )) iv(X3) twostep robust In this example lagged value of dependent variable and variable X2 are How to apply xtabond2 in STATA? lagged the dependent variable or not and how much lag limits I should use in gmmstyle command. The precise measure is the absolute value of the year-on-year change in the percentage deviation of the expenditure share from trend calculated using a Hodrick-Prescott the implementation. is quadratic in T . The Moreover, the GMM coefficient for the lagged dependent variable seems to behave as. 23 Dec 2018 in lag limits. Relationship between Gender Inequality and Development. 86-136. More precisely, the amount of the local tax cannot exceed the threshold value per square meter (or per vehicle), as defined by the central legislation. Ioannis Bournakis, Middlesex University, United Kingdom Dr. ) in columns 2 and 4. Horowitz, and M. Bodnar, and A. ssrrn. 3 Apr 2012 1. n L(0/1). Northern Africa (5) 5 3 1. The techniques and their implementation in Stata, a statistical software package widely used in the research community, are an important input to the careful applied research CGD advocates. Thus, l. The coefficients, the significant variables, and the significance levels do not change a lot whether standard or robust errors are used, hence the results for which the specification tests pass with high p-values are shown in Table 8 . The lagged dependent variable is instrumented, while the lagged independent explanatory variable is not instrumented. profits) using Belgian linked panel data. B. 10 Dec 2013 that typically results in a large number of overidentifying restrictions. Fiscal rules are a key political institution that entrench austerity as a permanent feature of government budgetary policy. blogger. Cano-Urbina. 103, Center for Global Development (CGD), Washington DC. Working Paper Number 103 December 2006 How to Do xtabond2: An Introduction to “Difference” and “System” GMM in Stata By David Roodman Abstract The Arellano-Bond (1991) and Arellano-Bover (1995)/Blundell-Bond (1998) linear generalized method of moments (GMM) estimators are increasingly popular. Robust standard  This section also highlights the limitations and specifies avenues for the use of four lags for controlling the endogeneity problem in estimating a regression model In order to obtain estimates of System GMM we apply xtabond2 in Stata   variables with their lags (see Roodman, 2009; Arellano and Bond, 1991). Telephone international: +46 8 787 01 00 . In response to the global financial crisis of 2007–2009, risk-based capital requirements have been reinforced in the new Basel III Accord to counter excessive bank risk-taking behavior. year) robust twostep xtabond2 DepVar l. and Portela M. “Initial Conditions and Moment Restrictions in Dynamic. Journal of Educational Psychology 66: 688-701. I use the Stata command xtabond2 (Roodman, 2009a) to derive System GMM The lagged DVs, along with public and private infrastructure investment, are I collapse the instrument matrix and impose instrumental variable lag limits that  In the difference-GMM estimates, lagged values of the independent variables were used (pca) to the instruments and limit the number of instruments by retaining 24 The collapse option in Stata's xtabond2 command performs this, and the  18 Jul 2019 by the development of the Stata package Xtabond2 (StataCorp LLC, College Station, many implicit or explicit coefficient restrictions, but does limit in a from the dependent variable then the first lag of such a regressor must  15 Nov 2017 The basic problem with the lagged dependent variable included in \(\text{pli}{{\ text{m}}_{n\to \infty }}\frac{1}{NT}\sum\limits_{i=1}^{N}{\sum\limits_{t=1}^{T}{\left( Beside the xtabond,we also can use the user-written xtabond2  31 Aug 2015 mates and, when associated also with the limitation of the lags, with a We use the command xtabond2 for GMM estimation of dynamic panel  balance limits the scope for fiscal stimulus and can potentially lead to a Greek- like sovereign debt crisis. 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(2009b) A Note on the Theme of Too Many Instruments, Oxford Bulletin on Economics and Statistics, 71(1), pp. 2+6∗7/2 = 23 for the example above 12 / 32 xtabond2 can fit two closely related dynamic panel data models. Findings highlight that educational credentials have a stronger impact on productivity than on wage costs. Prof. The But distance can also be important because rapid urbanization leads to congestion, and divisions within cities can be manifest in slums and ghettos. Review of International Economics, 9(3):531-546. Abbreviations and symbols used 188 2. Next it shows how to apply these estimators with xtabond2. 05≤p(Hansen This working paper by CGD research fellow David Roodman provides an introduction to a particular class of econometric techniques, dynamic panel estimators. We know very little about the relationship between size and the duration of funding and subsequent research performance. se . 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Apr 16, 2020 · Different purchase limits apply for electronic savings bonds and paper savings bonds. pca2: implementing a strategy to reduce the instrument count in panel GMM Maria Elena Bontempi Irene Mammi† August 27, 2014 Abstract The problem of instrument proliferation and its consequences (over-ﬁtting of the endogenous explanatory variables, biased IV and GMM es-timators, weakening of the power of the overidentiﬁcation tests) are This working paper by CGD research fellow David Roodman provides an original synthesis and exposition of the literature on a particular class of econometric techniques called "dynamic panel estimators," and presents the first implementation of some of these techniques in Stata, a statistical software package widely used in the research community. 其中gmmopt 为 gmmstyle(varlist [, laglimits(# #) collapse orthogonal equation(diff |level|both) passthru split]) 2. 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We achieve this, following Roodman (2006), both by limiting the number of lags we use and by collapsing the instrument matrix. variables and limits the lag depth to order 10. 回归时候可以使用 aweights, pweights, 和fweights  the lagged dependent variable may cause problems with estimation. the sphere of activities of the Riksbank that are considered . 09 Nov 2016, 02:26. P. (2009). If T is fairly large (more than 7–8) an unrestricted set of lags will introduce a huge number of instruments, with a possible loss of ef?ciency. Baby & children Computers & electronics Entertainment & hobby In Section 3, we provide a formal statement of the identifying assumptions as well as adiscussion of the appropriate lag structures. First, trade imports modulate FDI to Lag value of dependent is included as an independent variable, and it has a significant positive impact on current market leverage that shows model is dynamic. 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Towards a Health Economic Simulation Model of Type 2 Diabetes in Sweden . Sen, A. In the second part of the analysis, two stages system dynamic panel data models based on the studies of Arellano and Bover (1995) and Blundell and Bond (1998) were used. The Stata Journal 9(1) 86–136. of California - Davis (Based on This study assesses the simultaneous openness hypothesis that trade modulates foreign direct investment (FDI) to induce positive net effects on total factor productivity (TFP) dynamics. If T is fairly large (more than 78) an unrestricted set of lags will introduce a huge number of instruments, with a possible loss of efciency. Women, Work, and Economic Growth Leveling the - IMF eLibrary progress in recent decades, labor markets across the world remain divided . The matrix product T Q0 ΣQ = {2IT − (LT + L−1 T )} is a Toeplitz matrix. ,An index for financial development has been constructed using principal component analysis technique by including banking sector development, stock market development, bond market development and 5. y x1 x2 x3 x4 x5, robust gmm(l. to be of interest to a wider public. Useful Internet Links 209 LIST OF TABLES I. China, Asia, and the New World Economy This page intentionally left blank China, Asia, and the New World Economy Edited by Barry Eichengreen, Charles Wyplosz, and Yung Chul Park 1 3 Great Clarendon Street, Oxford ox2 6DP Oxford University Press is a department of the University of Oxford. xtabond2 discrepancy. Thus the first strategy restricts to the minimum the number of lagged values used to generate internal instruments for both the predetermined lagged dependent variable and the So in a model with one lag of the dependent variable, k strictly exogenous variables and p = T −2 periods from which to from moment equations, there are k +p ∗ (p +1)/2 moment conditions. ). In addition, μ t and δ i are respectively time-specific and country-specific effects. Model 2 has 24 instruments while How2Do_xtabond2_经济学_高等教育_教育专区 617人阅读|55次下载. Sign up to join this community There is now a new version of xtabond2 that takes advantage of the fast Mata programming language in Stata 9. The following will produce the same point estimates: webuse abdata, clear xtabond2 n L. GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. ADB does not guarantee the accuracy of the data included in this publication and accepts no 11 How Pervasive is Clientelist Politics in the Pacific? 15 The Political Economy of Sugar Rents in Fijiâ by Satish Chand. l. com Blogger 30 1 25 tag:blogger. It would be desirable to limit # of lags in (1) it z . 135-58. xtabond2 lag limits

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# Building an "off grid" facility ran off large 3 phase genny. Need batteries and inverter thoughts.

#### dknguyen

##### Well-Known Member
Have I missed something here?, it would cost too much to run electricity to the property (fair enough), but it's viable to run gas to the property?, or are you talking about trucking gas (or indeed diesel) to the property long term.

A friend of mine bought a fairly big generator from an auction a number of years back, I can't remember the size but it was pretty substantial, and was a two stroke diesel. It came from an American Airforce base in the UK - and was presumably sized to power the entire base?. I remember at the time we decided it was big enough to power the town we were in, about 15,000 people.

He sold it quite easily, and made a decent profit.
How big is such a generator?

#### KeepItSimpleStupid

##### Well-Known Member
Take a look at www.xantrex.com for inverter/charger/generator stuff.

Battery charging may only be for a certain chemistry though.

#### fastline

##### Member
I don't see anything higher voltage than 24V? At the capacities I am talking about, I really need to be pushing the voltage up which should reduce costs everywhere. Wire, electrics, etc. I haven't really chased an inverter yet but never seen one offered in the USA that is actually affordable. Its pretty ridiculous to see a $5000 inverter for 5KW when I can get a complex 50HP, 3p, 480V VFD for$1000 or less. Inverter price is just a little nutty.

I am still looking at battery options. I cannot even understand the stuff from China. No clue what is being offered. They say "set", but what in the world is that and what is the price? I highly doubt I will anything that makes financial sense in the USA.

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## Wire Solver

The following is an abbreviated description of the derivation of the equations solved for by the wire solver. For more detailed information, see [1].

For PEC (Perfect electrically conducting) wires, the boundary conditions require the tangential component of the total electric field on the wire surface to be zero:

You can also express the equation in terms of the surface current density, ${\stackrel{\to }{J}}_{s}$, on the PEC wire and its spatial derivative. This is done by integrating the effect of the surface current density using a Green's function, $g\left(|\stackrel{\to }{r}-{\stackrel{\to }{r}}^{\text{'}}|\right)$. The Green's function abstractly represents the effect of an infinitesimal surface-current density source located at ${\stackrel{\to }{r}}^{\text{'}}$ on the electric and magnetic fields at an observation point $\stackrel{\to }{r}$. The Green's function for free space propagation is:

where $k=\omega \sqrt{{\epsilon }_{0}{\mu }_{0}}$ is the wave number and ω is the angular frequency. In general, the following steps are needed to solve the electromagnetic (EM) problem and obtain the EM fields in the medium. To represent the EM problem accurately, both longitudinal and transverse components of integrated current are taken into consideration on the wire surface and require that Eq. (1) holds over the entire wire surface. Discretize Eq.(1) over a finite set of points or basis functions to obtain a set of equations. Discretize the surface current-density into a finite set of basis functions to obtain a set of unknowns. Solve the set of equations of unknowns to yield a discrete approximation to the surface currents-densities on the wire. These current densities enables calculation of the electromagnetic fields at any desired point. For thin wires the above steps are exhaustive and, simplify the Green's function to :

also referred to as the thin-wire kernel approximation, where ${r}_{a}=\sqrt{{r}^{2}+{a}^{2}}$ is an approximate average of the distance $|\stackrel{\to }{r}-{\stackrel{\to }{r}}^{\text{'}}|$, r is the distance between the infinitesimal surface current-density source and the wire axis, and a is the wire radius. In addition, the current density on the wire is replaced by the wire current $I=2\pi a|{\stackrel{\to }{J}}_{s}|$|. Using the above approximation, write Eq. (1) as:

where s is the longitudinal location along the wire and $\stackrel{\to }{e}\left(s\right)$ is the unit vector representing the wire orientation at that location. Discretize the wire into a finite number of segments s(m) where m = `1....N`, and then further discretize Eq.(4) into a finite set of equations imposed at points matching p = `1....N` to obtain:

where Im(sm) is the current distribution along the segment m approximated by the polynomial of the form:

with hm being the length of the segment and nm the chosen degree of the polynomial (which is different from segment to segment). Substituting Eq. (6) into (5), the set of equations can be written in a matrix format as:

where [Zp,mi] is the impedance matrix, [Imi] is the vector of unknown coefficients representing the current on the wire, and [Vexp,p] is the excitation vector. More details about the calculation of the elements of [Zp,mi] are given in [1].

## References

[1] Popovic,B.C, M.B. Dragovic and A.R. Djordjevic. Analysis and Synthesis of Wire Antennas Research Studies Press, 1982


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141 views

No of 5 letter english  words that contains atleast one 'a'  ?

i used the approch that

With 26 alphabet for a 5 letter word we can have $26^{5}$ possible words as each 5 position can have 26 possible alphabet.

we need no of word which contains at least one ‘A’.

This is same as

Total number of words – Number of words with no ‘A’

Now,

Number of words with no ‘A’ =$25^{5}$ as, each 5 position can have 25 possible alphabet as we exclude ‘A’.

so ,

Total number of words which contains at least one ‘A’ =$26^{5}-25^{5}$.

i have also same idea as you solve this question but i tried a different approch that does not work , image of my solution is given above plese tell me my mistake , your answer is right
you have over count the number of words.

Case 1:- a_ _ _ _

here ‘aaaaa’ was counted.

case 2:- _a_ _ _

here also ‘aaaaa’ was counted .

same for other cases also happen.

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279 views
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# Search for $\mbox{B}^0_s-\overline{\mbox{B}^0_s}$ oscillations and a measurement of $\mbox{B}^0_d-\overline{\mbox{B}^0_d}$ oscillations using events with an inclusively reconstructed vertex

Abstract : Neutral B meson oscillations in the $\mbox{B}^0_s-\overline{\mbox{B}^0 _s}$ and $\mbox{B}^0_d-\overline{\mbox{B}^0_d}$ systems were studied using a sample of about 4.0 million hadronic Z decays recorded by the DELPHI detector between 1992 and 2000. Events with a high transverse momentum lepton were removed and a sample of 770 k events with an inclusively reconstructed vertex was selected. The mass difference between the two physical states in the $\mbox{B}^0_d-\over$ system was measured to be: \begin{center} $\Delta m_d = (0.531 \pm 0.025 (stat.) \pm 0.007 (syst.)) \rm ps^{-1}$. \end{center} The following limit on the width difference of these states was also obtained: \begin{center} $|\Delta\Gamma_{\rm B_d}| / \Gamma_{\rm B_d} 0.18$ at 95\% CL. \end{center} The corresponding sensitivity of this analysis is equal to 6.6 ps$^{-1}$.
Document type :
Journal articles

Cited literature [6 references]

http://hal.in2p3.fr/in2p3-00021508
Contributor : Sylvie Flores Connect in order to contact the contributor
Submitted on : Friday, May 23, 2003 - 9:01:54 AM
Last modification on : Tuesday, January 25, 2022 - 12:48:05 PM
Long-term archiving on: : Tuesday, June 2, 2015 - 1:10:38 PM

### Citation

J. Abdallah, P. Abreu, W. Adam, P. Adzic, T. Albrecht, et al.. Search for $\mbox{B}^0_s-\overline{\mbox{B}^0_s}$ oscillations and a measurement of $\mbox{B}^0_d-\overline{\mbox{B}^0_d}$ oscillations using events with an inclusively reconstructed vertex. European Physical Journal C: Particles and Fields, Springer Verlag (Germany), 2003, 28, pp.155-173. ⟨10.1140/epjc/s2003-01183-7⟩. ⟨in2p3-00021508⟩

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Question

# What is limiting reagent ?

Solution

## Limiting reagent in a chemical reaction is the substance that is totally consumed when the chemical reaction is complete.The amount of the product formed is limited by this reagent, since the reaction cannot continue without it.eg. suppose, 1 more of hydrogen and 1 more of oxygen take part in the reaction   $$2H_{2} + O_{2} \rightarrow 2H_{2}O$$The limiting reagent would be hydrogen because the reaction uses up hydrogen twice as fact as oxygen.Chemistry

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# A Black hole as topological insulator

1. Apr 3, 2017

### shuijing

Hi, is anyone familiar with topological insulator? I read an interesting paper:
http://arxiv.org/abs/1703.09365,
Black hole as topological insulator

Abstract: Black holes are extraordinary massive objects which can be described
classically by general relativity, and topological insulators are new phases of
matter that could be use to built a topological quantum computer. They seem to
be different objects, but in this paper, we claim that the black hole can be
considered as a kind of topological insulator. For BTZ black hole in three
dimensional $AdS_3$ spacetime we give two evidences to support this claim: the
first evidence comes from the black hole "membrane paradigm", which says that
the horizon of black hole behaves like an electrical conductor. On the other
hand, the vacuum can be considered as an insulator. The second evidence comes
from the fact that the horizon of BTZ black hole can support two chiral
massless scalar field with opposite chirality. Those are two key properties of
2D topological insulator. For higher dimensional black hole the first evidence
is still valid. So we conjecture that the higher dimensional black hole can
also be considered as higher dimensional topological insulators. This
conjecture will have far-reaching influences on our understanding of quantum
black hole and the nature of gravity.

I am familiar with black hole but not topological insulator. Can anyone explain it to me?

2. Apr 3, 2017

### ZapperZ

Staff Emeritus
You're barking at the wrong tree.

Topological insulator is a topic in condensed matter physics, and a very active one too. There have been a few threads started in the condensed matter forum on topological insulators. So you may want to browse that forum first, or ask this question there (see if a Mentor will move this thread for you).

Zz.

3. Jun 7, 2017

### DeathbyGreen

Wow this sounds interesting! btw, Zapperz, this is the condensed matter forum, right? :D An insulator is simply a material which doesn't conduct electricity. In the system's band structure, the valence and conduction bands are separated by an energy gap which (assuming it is large enough) prevents electrons from jumping between bands. In condensed matter we use the Hamiltonian to describe a system; a few years ago the idea came around to classify these Hamiltonians according to their topology. This is usually done by considering $H = h(k)\tilde{\sigma}$, and using the $h(k)$ (or some other vector, it is somewhat up to the physicist) and finding it's map onto a unit sphere. The number of times this vector wraps around the unit sphere during the momentum shifting from $-\pi\rightarrow\pi$ in the Brillouin zone (band structure) is known as the winding number, or Chern number (similar to a genus in pure mathematics).

It was discovered that in certain systems, predicting the topology can correspond to protected edge states. So in some insulators which were previously thought to contain no conductance, two edge modes appear (under certain parameters) which are protected (not affected by disorder and giving conductance quantized similar to the quantum hall conductance) and move antiparallel to each other (chiral). A VERY nice review on the topic can be found in Topological Insulators, by Hasan and Kane.

Regarding the vacuum question, this is addressed directly in the Hasan and Kane review. The idea is that a vacuum is an insulator, with a gap separating the particle and antiparticle states. So if a black hole is a vacuum with chiral edge modes around the perimeter, the author's should be suggesting that this system can be classified topologically; it is an overall insulator but contains currents propagating in antiparallel directions on the edge. Whether these are protected states would interesting to see. Check out that review!

Last edited: Jun 7, 2017
4. Jun 7, 2017

### ZapperZ

Staff Emeritus
The thread was moved from where it was originally posted.

Zz.

5. Jul 12, 2017

### muscaria

Here's a nice 2 min video on topological insulators


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# Tag Info

3

Very interesting question. I am not an expert on the subject, however, I was able to find a collection of papers on the subject that should get you started. Here is a good and very informative paper that walks you through several tick by tick volatility estimators that seek to reduce the volatility imposed by market micro-structure: Efficient estimation of ...

1

For any continuous distribution we can define $$VaR_{\alpha}=-F^{-1}(1-\alpha)$$ where $F^{-1}$ is the inverse of the CDF. Now suppose that you have a distribution which comes from a location-scale family with location parameter $\mu$ and scale parameter $\sigma$ then $$F^{-1}(1-\alpha)=\mu+\sigma \phi^{-1}(1-\alpha)$$ where $\phi^{-1}$ is the inverse CDF ...

1

Both approaches can be useful. For stocks, sorting into quantiles is popular because it's easy to understand and explain it's a simple matter to build factor portfolios and track or backtest their performance, while the translation from expected returns to a portfolio is a bit more involved more robust than a single-stock regression, because it is less ...

1

The chart you linked to offers data for the "instantaneous forward rate" which are the rates you are looking for (f(tj,tj+τk)). Regarding the construction of the zero-coupon yield curves (cited from the ECB website): "The ECB estimates zero-coupon yield curves for the euro area and derives forward and par yield curves. A zero coupon bond is a bond that ...

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# Evaluate the integrals without using tables: \int_{-\infty}^{\infty}\frac{2x dx}{(x^{2}+1)^{2}}

The integrals converge. Evaluate the integrals without using tables.
${\int }_{-\mathrm{\infty }}^{\mathrm{\infty }}\frac{2xdx}{{\left({x}^{2}+1\right)}^{2}}$
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After a little bit of a delay, I’m back to writing a little bit more about theory of computation. (Be warned that this post will assume more prior knowledge about automata than the previous entry.) So far, we’ve been learning a lot about languages, which are a set of strings formed from some alphabet (e.g. 0 and 1 for binary numbers) that obey certain guidelines. Languages can be classified as either regular or non-regular. Regular languages are those that can be recognized by some DFA, and I made some examples of that in the first Theory post. But not all languages are regular. And so far, I believe there’s three main ways to prove a language is not regular.

1. Closure properties of regular languages (unions, intersections, concatenations, “star” operation, etc.)
2. The Pumping Lemma
3. The Myhill-Nerode Theorem and Fooling Sets

The usefulness of these three depends on the language. For some, the closure properties are the easiest to prove non-regularity; for others, it might be the Myhill-Nerode theorem. In fact, there are some languages that are not regular, yet are satisfied by the Pumping Lemma! That lemma is not a sufficient condition on non-regularity, so if a language satisfies it, all bets are off as to whether it’s regular or not. But if a language “passes” the requirements of Myhill-Nerode, it must be regular. Clearly, languages require multiple strategies to prove regularity or non-regularity.

I thought I’d present an example of  a non-regular language and see how all three methods could be applied. First, before we begin, the canonical non-regular language (meaning, the one language that often introduces students into the world of linguistic non-regularity) is the following:

$A = \{0^n1^n \mid n \ge 0\}$

It’s the language consisting of all strings with an equal amount of zeroes and ones, with the ones following the zeroes. Intuitively, it’s fairly simple to see that it’s non-regular. If a DFA were to recognize this language, it would have to compute the total amount of zeroes, followed by the ones. Consequently, since there would be an infinite amount of states needed, we can’t make a DFA since they are meant to be finite automata. That is, they have finitely many states. We will use this knowledge in hand, combined with the three common ways to prove non-regularity, when we consider this similar language:

$B = \{0^m1^n \mid m \ne n\}$

It’s similar, but we just have to make sure that there are a different amount of zeroes and ones, and again, that the ones all come after the zeroes.

So let’s consider the different ways we could prove that this language is not regular.

Closure Properties

First, we look at closure properties of regular languages. A theorem of regular languages is that they are equivalent to the class of regular expressions. We know that $0^*$ and $1^*$ are both regular expressions. Furthermore, a theorem states that the class of expressions is closed under concatenation, so the following regular expression (i.e. regular language) $0^*1^*$ is regular! Notice the key difference between this language and the previous two; the fact that we don’t have restrictions on the amount of 0s and 1s makes it possible to construct a DFA for this! Such a DFA would be fairly simple to construct — it would only require three states, one to start and represent the initial zeroes, one to represent the ones, and another to represent the death state, which is when, at any point, we see a 0 following a 1.

Why is knowing $0^*1^*$ important? The class of regular languages is closed under intersection, so consider the language

$\overline{B} \cap 0^*1^* = \{0^k1^k \mid k \ge 0\}$

Where $\overline{B}$ represents the complement of $B$. Yet another theorem is that regular languages are closed under complements. That is, if $B$ is regular, then $\overline{B}$ is regular. But notice that if we assume $B$ is regular, then the intersection $\overline{B} \cap 0^*1^*$ must be regular by intersection closure. But we know that the intersection is equal to the canonical non-regular language! Hence, $B$ must be non-regular.

The Pumping Lemma

That wasn’t too bad, but things will get slightly more complex when we use the pumping lemma. We assume, by way of contradiction, that $B$ is regular. Then by the pumping lemma, there exists some string length $p$ such that any string in this language that is at least this long can be partitioned into components $x, y, z$. Consider the string $s = 0^p1^{p! + p} \in B$, which clearly satisfies the minimum length requirement, so it can be pumped. We set $x = 0^a, y = 0^b, \mbox{ and } z = 0^{c}1^{p!+p}$, where $b \ge 1 \mbox{ and } a+b+c = p$. Let us pump the $y$ component $i +1 = p!/b + 1$ times in $s' = xy^{i+1}z$, which must be in the language by the pumping lemma. But pumping this string turns out to be $s' = 0^{a+b+c+p!}1^{p!+p} = 0^{p!+p}1^{p!+p} \not \in B$, a contradiction. Any language that fails the pumping lemma is not regular, so $B$ is non-regular.

The Myhill-Nerode Theorem

Knowing how to use the pumping lemma after reading the solution seems simple, but the hard part is actually coming up with the $p! + p$ component. We wrap up by using the often easier Myhill-Nerode method to prove that this language is not regular. Let’s use the fooling set $F = \{0^i \mid i \ge 0\}$. Then for any distinct $x, y \in F$, we know that the have a different amount of zeroes in them. Let $x = 0^j \mbox{ and } y = 0^k$ Then take $z = 1^j$. We know that $xz \not \in B$, but we also have $yz \in B$ … so these strings are distinguishable from each other! And since our fooling set is infinite, and any pairs of distinct strings in it are distinguishable, any DFA would have to have an infinite amount of states, which is impossible. Hence, this language is not regular.

(Personally, I prefer the fooling set method to solving problems … it’s often very simple, and the same fooling sets can be used to prove non-regularity for multiple languages.)

Up next in my studies are context-free grammars. Stay tuned!

(On a side note, this is my 50th blog entry.)


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# A stereographic manipulation

Algebra Level 3

Let $$S^1 = \{ (x,y) \in \mathbb{R} \backslash x^2+y^2 = 1 \}$$. Consider the stereographic projection :

Let $$\mathcal{L}$$ be the line passing through the point $$N=(0,1) \in S^1$$ and some point $$P=(x,y) \in S^1$$ such that $$(x,y) \neq (0,1)$$. Then $$\mathcal{L}$$ crosses the x-axis at a point $$P'=(\overline{x},0)$$. This defines a mapping : $f : S^1 \backslash \{ (0,1) \} \rightarrow \mathbb{R}$ $(x,y) \mapsto \overline{x}=f(x,y)$

Now, do the same, but this time, with the line $$\mathcal{L'}$$ passing through the point $$(0,-1) \in S^1$$. Call the new function it induces by $$f'$$.

What is $$(f+f')(\frac{1}{\sqrt{2}},\frac{1}{\sqrt{2}} )$$?

×


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# Identified charged hadron production in p+p collisions at sqrt(s)=200 and 62.4 GeV

Abstract : Transverse momentum distributions and yields for $\pi^{\pm}$, $K^{\pm}$, $p$ and $\bar{p}$ in $p+p$ collisions at $\sqrt{s}$=200 and 62.4 GeV at midrapidity are measured by the PHENIX experiment at the Relativistic Heavy Ion Collider (RHIC). These data provide important baseline spectra for comparisons with identified particle spectra in heavy ion collisions at RHIC. We present the inverse slope parameter $T_{\rm inv}$, mean transverse momentum  and yield per unit rapidity $dN/dy$ at each energy, and compare them to other measurements at different $\sqrt{s}$ in $p+p$ and $p+\bar{p}$ collisions. We also present the scaling properties such as $m_T$ scaling, $x_T$ scaling on the $p_T$ spectra between different energies. To discuss the mechanism of the particle production in $p+p$ collisions, the measured spectra are compared to next-to-leading-order or next-to-leading-logarithmic perturbative quantum chromodynamics calculations.
Document type :
Journal articles
Domain :

http://hal.in2p3.fr/in2p3-00564214
Contributor : Dominique Girod <>
Submitted on : Tuesday, February 8, 2011 - 12:03:33 PM
Last modification on : Thursday, February 25, 2021 - 10:58:31 AM

### Citation

A. Adare, S. Afanasiev, C. Aidala, N. N. Ajitanand, Y. Akiba, et al.. Identified charged hadron production in p+p collisions at sqrt(s)=200 and 62.4 GeV. Physical Review C, American Physical Society, 2011, 83, pp.064903. ⟨10.1103/PhysRevC.83.064903⟩. ⟨in2p3-00564214⟩

Record views


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# torch_logaddexp: Logaddexp In torch: Tensors and Neural Networks with 'GPU' Acceleration

## Usage

 1 torch_logaddexp(self, other)

## Arguments

 self (Tensor) the input tensor. other (Tensor) the second input tensor

## logaddexp(input, other, *, out=None) -> Tensor

Logarithm of the sum of exponentiations of the inputs.

Calculates pointwise \log≤ft(e^x + e^y\right). This function is useful in statistics where the calculated probabilities of events may be so small as to exceed the range of normal floating point numbers. In such cases the logarithm of the calculated probability is stored. This function allows adding probabilities stored in such a fashion.

This op should be disambiguated with torch_logsumexp() which performs a reduction on a single tensor.

## Examples

 1 2 3 4 5 6 if (torch_is_installed()) { torch_logaddexp(torch_tensor(c(-1.0)), torch_tensor(c(-1.0, -2, -3))) torch_logaddexp(torch_tensor(c(-100.0, -200, -300)), torch_tensor(c(-1.0, -2, -3))) torch_logaddexp(torch_tensor(c(1.0, 2000, 30000)), torch_tensor(c(-1.0, -2, -3))) }

torch documentation built on Oct. 7, 2021, 9:22 a.m.


text:
REST API to filter Document Library based on people and groups column

I have the custom document library with a people and groups columns.So, whenever the user uploads a doc in the library, manual they will specify any SharePoint group name in the people and group column.Now I would like to filter the document library files based on the groups.Below end point, i tried in my scenario, but no luck

End Point URL :"/_api/web/lists/getbytitle('DocName')/files?$filter=groupNameId eq 2" here "groupName" is original column name(People and Groups).Since I am trying to filter doc based on the group id, I used "groupNameId" and Here "2" is the group Name ID. 1 Answer You can do it as below "_api/web/lists/getbytitle('DocName')/files?$expand=groupName&\$filter=groupName/Id eq 2"

• I tried your end point.But no luck,its throwing "<m:message xml:lang="en-US">Specified method is not supported.</m:message>" – user52682 Jul 7 '16 at 6:36


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# Redirect domain during certain time of the week

Please bear with me, I am pretty new to Joomla, and I only have a slightly operational knowledge of web design.

So here's what I want to do; Our church streams our sermons every sunday morning from about 10:30 to about 12:30. I want to redirect all pages under our domain (with the exception of the admin page) to the live stream url. I know it's probably just a matter of throwing together a script, but I lack the proficiency to do so from scratch. If someone could just get me started, I think I could tweak whatever parameters I need to to make it do what I want.

Thanks!

Maybe not the most elegant solution, but you can add the following code to the beginning of your templates index.php file (located in ROOT/templates/YOURTEMPLATE/index.php):

<?php
$hour = date('G');$minute = date('i');
$day = date('w');$m = $hour * 60 +$minute; // Minutes since midnight.
if(
$day == 0 // Sunday... &&$m >= 630 // ... after 10:30…
&& \$m <= 750 // ... but before 12:30…

This should redirect all your visitors to http://example.com every Sunday between 10:30 and 12:30.
• +1 for the answer, however I would recommend making a small plugin for this rather than editing the template's index.php. At least that way no changes will be overridden and it can easily be disable if need be ;) – Lodder May 4 '15 at 17:21


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Directions(1-9): Solve the given questions

1. A man leaves for his office from his house.He walks towards East.After moving a distance of 20 m ,he turns South and walks 10 m.Then he walks 35 m towards the West and further 5 m towards the North .He then turns towards East and walks 15 m .What is the straight distance between his initial and final positions?
A.0
B.5
C.10
D.None of these

2. Rohan walks a distance of 3 km towards North,then he turns to his left and walks for 2 km .He again turns left and walks for 3 km .At this point he turns to his left and walks for 3 km.How many km is he from the starting point?
A.1 km
B.2 km
C.3 km
D.5 km

3. Manick walked 40 m towards North,took a left turn and walked 20 m .He again took a left turn and walked for 40 km.How far and in which direction is he from the starting point?
A.20 m East
B.20 m North
C.20 m South
D.20 m West

4. Namita walks 14 m towards west,then turns to her right and walks 14 m and then turns to her left and walks 10 m.Again turning to her left she walks 14 m .What is the shortest distance between her starting point and the present position?
A.10
B.24
C.28
D.38

5. Amit walked 30 m towards East, took a right turn and walked 40 m. Then he took a left turn and walked 30 m. In which direction is he now from the starting point?
A.North-East
B.East
C.South-East
D.South

6. A villager went to meet his uncle in another village situated 5 km away in the North-East direction of his own village.From there he came to meet his father-in-law living in a village situated 4 km in the south of his uncle’s village. How far away and in what direction is he now?
A.3 km in the North
B.3 km in the East
C.4 km in the East
D.4 km in the west

7. Sanjeev walks 10 m towards the South. Turning to the left, he walks 20 m and then moves to his right. After moving a distance of 20 m,  he turns to the right and walks 20 m.Finally, he turns to the right and moves a distance of 10 m. How far and in which direction is he from the starting point?
A.10 m South
B.10 m North
C.20 m South
D.20 m North

8. I am facing South.I turn right and walk 20 m. Then I turn right again and walk 10 m. Then I turn left and walk 10 m and then turning right walk 20 m.Then, I turn right again and walks 60 m.In which direction am I from the starting point?
A.North
B.North-West
C.East
D.North-East

9. A man walks 1 km towards East and then he turns to South and walks 5 km.Again he turns to East and walks 2 km, after this he turns to North and walks 9 km. Now, how far is he from his starting point?
A.3 km
B.4 km
C.5 km
D.7 km

Solution


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Proving $f_n(z)=\frac{nz}{1+n^3z^2}$ converges uniformly

Show that the sequence of functions $$f_n(z)=\frac{nz}{1+n^3z^2}$$ converges uniformly on the set $$E=[1,\infty]$$.

$$\lim_{n\to\infty}\frac{nz}{1+n^3z^2}=0$$ so it converges pointwise to 0. So I am going to check if it converges uniformly to $$0$$.

$$|\frac{nz}{1+n^3z^2}-0|\leqslant |\frac{nz}{n^3z^2}|=|\frac{1}{n^2z}|\leqslant\frac{1}{n^2}\to 0$$ as $$n\to\infty$$

since $$|\frac{nz}{1+n^3z^2}-0|$$ is majored by $$\frac{1}{n^2}$$ that does not depend on $$z$$. I conclude the function converges uniformly to $$0$$.

Questions:

Is this proof right? If not why? Which are the alternatives?


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obsidian

HDU 2817 A sequence of numbers(快速幂)

18
2017/08

题目

Description

Xinlv wrote some sequences on the paper a long time ago, they might be arithmetic or geometric sequences. The numbers are not very clear now, and only the first three numbers of each sequence are recognizable. Xinlv wants to know some numbers in these sequences, and he needs your help.

Input

The first line contains an integer $N$ , indicting that there are $N$ sequences. Each of the following $N$ lines contain four integers. The first three indicating the first three numbers of the sequence, and the last one is $K$ , indicating that we want to know the $K$-th numbers of the sequence.

You can assume $0 < K \leq 10^9$ , and the other three numbers are in the range $[0, 2^{63})$ . All the numbers of the sequences are integers. And the sequences are non-decreasing.

Output

Output one line for each test case, that is, the $K$-th number module ($\%$) $200907$ .

Sample Input

2
1 2 3 5
1 2 4 5

Sample Output

5
16

代码

#include<iostream>
#include<cstdio>
#include<cstring>
#include<string>
#include<algorithm>
#include<queue>
#include<stack>
#include<vector>
#include<cmath>
#include<set>
#include<map>
#include<cstdlib>
#include<functional>
#include<climits>
#include<cctype>
#include<iomanip>
using namespace std;
typedef long long ll;
#define INF 0x3f3f3f3f
#define clr(a,x) memset(a,x,sizeof(a))
const double eps = 1e-6;
const int mod=200907;
ll quick_mod(ll a,ll n,int mod)
{
ll t=1;
for(;n;n>>=1,a=(a*a%mod))
if(n&1)
t=(t*a%mod);
return t;
}
int main()
{
int t;
cin>>t;
double a,b,c;
ll n;
while(t--)
{
cin>>a>>b>>c>>n;
if(a+c==2*b)
{
ll a1=a;
ll d=(b-a);
ll ans=(a1%mod+((n-1)%mod)*(d%mod))%mod;
printf("%lld\n",ans);
}
else
{
ll a1=a;
ll t1=a1%mod;
double q1=b/a;
ll q2=q1;
ll q=q2%mod;
ll tmp=quick_mod(q,n-1,mod);
ll ans=(t1*tmp)%mod;
printf("%lld\n",ans);
}
}
return 0;
}

Last modification：November 2nd, 2019 at 03:01 pm


text:
History

Help on query formulation
$\text{SO}(4)$ and $S^3$. ($\text{SO}(4)$ och $S^3$.) (Swedish. English summary)
Normat 55, No. 3, 136-137, 144 (2007).
Summary: The 3-dimensional sphere can be thought of as a union of two solid tori glued along their boundaries. Those come from torus-fibrations, and this short note explores some elementary facts of how $\text{SO}(4)$ operates on them with connections to Hopf fibrations and quaternionic multiplication.
Classification: H75


text:
# Chapter 4 Ordered and unordered factors

A factor is a vector object used to specify a discrete classification (grouping) of the components of other vectors of the same length. R provides both ordered and unordered factors. While the “real” application of factors is with model formulae (see Contrasts), we here look at a specific example.

### 4.1 A specific example

Suppose, for example, we have a sample of 30 tax accountants from all the states and territories of Australia14 and their individual state of origin is specified by a character vector of state mnemonics as

> state <- c("tas", "sa",  "qld", "nsw", "nsw", "nt",  "wa",  "wa",
"qld", "vic", "nsw", "vic", "qld", "qld", "sa",  "tas",
"sa",  "nt",  "wa",  "vic", "qld", "nsw", "nsw", "wa",
"sa",  "act", "nsw", "vic", "vic", "act")

Notice that in the case of a character vector, “sorted” means sorted in alphabetical order.

A factor is similarly created using the factor() function:

> statef <- factor(state)

The print() function handles factors slightly differently from other objects:

> statef
[1] tas sa  qld nsw nsw nt  wa  wa  qld vic nsw vic qld qld sa
[16] tas sa  nt  wa  vic qld nsw nsw wa  sa  act nsw vic vic act
Levels:  act nsw nt qld sa tas vic wa

To find out the levels of a factor the function levels() can be used.

> levels(statef)
[1] "act" "nsw" "nt"  "qld" "sa"  "tas" "vic" "wa"

### 4.2 The function tapply() and ragged arrays

To continue the previous example, suppose we have the incomes of the same tax accountants in another vector (in suitably large units of money)

> incomes <- c(60, 49, 40, 61, 64, 60, 59, 54, 62, 69, 70, 42, 56,
61, 61, 61, 58, 51, 48, 65, 49, 49, 41, 48, 52, 46,
59, 46, 58, 43)

To calculate the sample mean income for each state we can now use the special function tapply():

> incmeans <- tapply(incomes, statef, mean)

giving a means vector with the components labelled by the levels

   act    nsw     nt    qld     sa    tas    vic     wa
44.500 57.333 55.500 53.600 55.000 60.500 56.000 52.250

The function tapply() is used to apply a function, here mean(), to each group of components of the first argument, here incomes, defined by the levels of the second component, here statef15, as if they were separate vector structures. The result is a structure of the same length as the levels attribute of the factor containing the results. The reader should consult the help document for more details.

Suppose further we needed to calculate the standard errors of the state income means. To do this we need to write an R function to calculate the standard error for any given vector. Since there is an builtin function var() to calculate the sample variance, such a function is a very simple one liner, specified by the assignment:

> stdError <- function(x) sqrt(var(x)/length(x))

(Writing functions will be considered later in Writing your own functions. Note that R’s a builtin function sd() is something different.) After this assignment, the standard errors are calculated by

> incster <- tapply(incomes, statef, stdError)

and the values calculated are then

> incster
act    nsw  nt    qld     sa tas   vic     wa
1.5 4.3102 4.5 4.1061 2.7386 0.5 5.244 2.6575

As an exercise you may care to find the usual 95% confidence limits for the state mean incomes. To do this you could use tapply() once more with the length() function to find the sample sizes, and the qt() function to find the percentage points of the appropriate t-distributions. (You could also investigate R’s facilities for t-tests.)

The function tapply() can also be used to handle more complicated indexing of a vector by multiple categories. For example, we might wish to split the tax accountants by both state and sex. However in this simple instance (just one factor) what happens can be thought of as follows. The values in the vector are collected into groups corresponding to the distinct entries in the factor. The function is then applied to each of these groups individually. The value is a vector of function results, labelled by the levels attribute of the factor.

The combination of a vector and a labelling factor is an example of what is sometimes called a ragged array, since the subclass sizes are possibly irregular. When the subclass sizes are all the same the indexing may be done implicitly and much more efficiently, as we see in the next section.

### 4.3 Ordered factors

The levels of factors are stored in alphabetical order, or in the order they were specified to factor if they were specified explicitly.

Sometimes the levels will have a natural ordering that we want to record and want our statistical analysis to make use of. The ordered() function creates such ordered factors but is otherwise identical to factor. For most purposes the only difference between ordered and unordered factors is that the former are printed showing the ordering of the levels, but the contrasts generated for them in fitting linear models are different.


text:
## Precalculus: Concepts Through Functions, A Unit Circle Approach to Trigonometry (3rd Edition)

$7$
Average rate of change from $a$ to $b$: $=\dfrac{f(b)-f(a)}{b-a}$ Wth $a=1$ and $b=3$: \begin{aligned} f(b)=f(3) &=3(3)^{2}-5(3) \\ &=3(9)-15 \\ &=27 - 15 \\ &=12 \\ \\f(a)=f(1) &=3(1)^{2}-5(1) \\ &=3-5 \\ &=-2\\ \\\text{substituting these values in the rate of change formula above yields}\\ \\&=\frac{12-(-2)}{3-1} \\ \\&=\frac{14}{2} \\ \\&=7\end{aligned}


text: A confidence interval is a range of values that describes the uncertainty surrounding an estimate. The most frequently used confidence intervals specify either 95% or 90% likelihood, although one can calculate intervals for any level between 0-100%. Our 90% confidence interval (CI) shows that the frequency of EZH2 mutations in the lymphoma patient population is between 20% and 30%. [11] Once an experiment is done and an interval calculated, this interval either covers the parameter value or it does not; it is no longer a matter of probability. CONFIDENCE INTERVALS. Confidence intervals can also be computed for many point estimates: means, proportions, rates, odds ratios, risk … Thank you for this question, indeed the interpretation of the confidence interval is different with this study because the outcome was a continuous variable, which was time. Interpretation: The odds of breast cancer in women with high DDT exposure are 6.65 times greater than the odds of breast cancer in women without high DDT exposure. This was calculated as the Geometric Least Square (GLS) mean, which for the purposes of this explanation we will consider to be simply a mean and ignore the GLS part. We indicate a confidence interval by its endpoints; for example, the 90% confidence interval for the number of people, of all ages, in poverty in the United States in 1995 (based on the March 1996 Current Population Survey) is "35,534,124 to 37,315,094." When you make an estimate in statistics, whether it is a summary statistic or a test statistic, there is always uncertainty around that estimate because the number is based on a sample of the population you are studying. The statistical interpretation is that the confidence interval has a probability (1 - $$\alpha$$, where $$\alpha$$ is the complement of the confidence level) of containing the population parameter. Thank you for reading! Understand and calculate the confidence interval. This gives the following interval (0.61, 3.18), but this still need to be transformed by finding their antilog (1.85-23.94) to obtain the 95% confidence interval. The confidence interval comes about as (in a computational notation) C(Sample(R(Theta))) Where C is a confidence interval construction function that takes a fixed set of values, Sample is a sampling function that pulls a random sample from an RNG, R is the RNG and Theta is the input parameter to the RNG. The p value interpretation is: Assuming the null hypothesis is true (shoe size does not predict penile length), the observed effect or more would occur 28% of the time. The correct way to interpret this statement is: There is a 90% chance that this particular confidence interval of [20% - 30%] contains the true population mutation frequency of EZH2 in lymphoma patients. Here is the list of all my blog posts. The other concept in precision is Confidence Intervals (CI). Published on August 7, 2020 by Rebecca Bevans. Confidence intervals contain key information that is necessary for the proper interpretation of many statistical analyses. A 95% confidence interval does not mean that for a given realized interval calculated from sample data there is a 95% probability the population parameter lies within the interval. Thus, the 95% confidence interval is the most common confidence interval to estimate in statistical inference. It is thus essential to understand and interpret confidence intervals correctly as a failure to do so could result in incorrect or … If someone asks me to interpret the confidence interval (say at the level of a first graduate course in statistics) -- are there typical templates for such an interpretation. By typical templates I mean something like this (and please feel free to edit if you have a better way of saying this): The said interval: Revised on January 7, 2021. For example, one might erroneously interpret the aforementioned 99% confidence interval of 70-to-78 inches as indicating that 99% of the data in …


text:
0
RESEARCH PAPERS

# Spreading Characteristics and Microscale Evaporative Heat Transfer in an Ultrathin Film Containing a Binary Mixture

[+] Author and Article Information
Sashidhar S. Panchamgam, Joel L. Plawsky

The Isermann Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180

Peter C. Wayner1

The Isermann Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180wayner@rpi.edu

1

Corresponding author.

J. Heat Transfer 128(12), 1266-1275 (Mar 26, 2006) (10 pages) doi:10.1115/1.2349506 History: Received August 23, 2005; Revised March 26, 2006

## Abstract

Using image-analyzing interferometry, the thickness profile, in the range of $δ0$ (adsorbed thickness) $<δ<3μm$, at the leading edge of a moving ultrathin film with phase change, was measured for a mixture of pentane-octane and compared to that of pure pentane. An improved data-analysis procedure was used to enhance the use of the measured thickness profile. There were significant differences between these two systems, demonstrating the presence of large Marangoni interfacial shear stresses with the mixture. A control volume model was developed to evaluate the differences between the pure fluid and the mixture. The disjoining pressure at the leading edge was found to control fluid flow in the evaporating pure system. However, due to Marangoni stresses, the effect of disjoining pressure on the mixture was found to be small at steady state for the fluxes studied. With an upstream bulk mixture of 2% octane and 98% pentane, a shear stress due to the gradient of the liquid-vapor interfacial surface tension resulting from distillation controlled fluid flow in the contact line region. The average curvature of the evaporating pseudo-steady state pure system was significantly larger (smaller length and larger apparent contact angle at $δ=0.1μm$) than the isothermal value, whereas the reverse occurred for the mixture. Using a continuum model, a comparison of numerically obtained Marangoni stresses and local evaporative heat flux profiles between the two systems was also made.

<>

## Figures

Figure 1

(a) Schematic diagram of the experimental setup, (b) cross-sectional view (line AB in (a)) of the quartz cuvette with inside dimensions 3mm×3mm. Gravity g is acting perpendicular to the cross section, and (c) cross-sectional view (line CD in (a)) of the quartz cuvette (inside dimensions 3mm×43mm).

Figure 2

Reflectivity images illustrating the movement of the binary mixture meniscus due to change in the heater power: (a) isothermal state (t=2.86s), (b) receding state (t=8.64s), (c) advancing state (t=20.54s), and (d) pseudo-steady state (t=336.1s). Reflectivity images were captured at an axial location of x≈0 (near the heater).

Figure 3

Illustration of the meniscus movement due to change in the heater power. I I′: Isothermal reference state, R-1: Receding cycle, and A-1: Advancing cycle, and a schematic of the control volume of an evaporating corner meniscus used for macroscopic interfacial force balance and continuum model.

Figure 4

Comparison of profiles of the distance traveled as a function of time of the pentane and the binary mixture menisci

Figure 5

Comparison of interfacial velocity profiles as a function of time of (a) the pentane meniscus and (b) the binary mixture meniscus

Figure 6

(a) Comparison of thickness profiles of the pentane meniscus at (1) isothermal state (t=0.07s), (2) advancing state (t=10.2s), and (3) pseudo-steady state (t=163.2s), and (b) expanded for contact line region (15)

Figure 7

(a) Comparison of thickness profiles of the binary mixture meniscus at (1) isothermal state (t=2.86s), (2) receding state (t=8.64s), and (3) pseudo-steady state (t=366.1s), and (b) expanded for contact line region

Figure 8

Comparison of curvature profiles of (a) the pentane meniscus and (b) the binary mixture meniscus

Figure 9

Comparison of adsorbed film-thickness profiles as a function of time of (a) the pentane meniscus and (b) the binary mixture meniscus. iso represents isothermal meniscus, min represents minimum, and avg represents an average value over the pseudo-steady-state regime

Figure 10

Comparison of profiles of the slope angle at δ=0.1μm as a function of time of (a) the pentane meniscus and (b) the binary mixture meniscus

Figure 11

Comparison of the maximum curvature profiles as a function of time of (a) the pentane meniscus and (b) the binary mixture meniscus

Figure 12

Comparison of various terms in Eq. 2 [A: 1.5δ2σ′∕3υ, D: 3βδσ′∕3υ, E: σδ3K′∕3υ, F: 3σδ2βK′∕3υ, and H: −12β(−Bavg)δ′∕3υδ3] for the mass flow rate equation for (a) the pentane and (b) the binary mixture menisci during nonisothermal (pseudo-steady) state for the adsorbed film region concentration, x1(L)=0.94

Figure 13

(a) dσ∕dy and (b) mole fraction of pentane (x1) as a function of meniscus length for the pentane (P) and the binary mixture (M) menisci during nonisothermal (pseudo-steady) state. x1 and σ′ profiles for the binary mixture meniscus in nonisothermal state were evaluated for the adsorbed film region concentration, x1(L)=0.94

Figure 14

Comparison of evaporative heat flux (q″) profiles of the pentane (P) and the binary mixture (M) menisci in isothermal and nonisothermal (pseudo-steady) states. The evaporative heat flux for the binary mixture meniscus in nonisothermal state was evaluated for the adsorbed film region concentration, x1(L)=0.94

Figure 15

Comparison of Π0,t∕Π0,0 between the pentane and the binary mixture menisci

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# A convenience store currently stocks 48 bottles of mineral water. The

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Intern
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Re: A convenience store currently stocks 48 bottles of mineral water. The  [#permalink]

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09 May 2017, 20:31
total ounce=35*48=1680
atq
(1680-40x)/(48-x)=25
x=32
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A convenience store currently stocks 48 bottles of mineral water. The  [#permalink]

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14 Apr 2018, 03:23
chetan2u Bunuel VeritasPrepKarishma niks18

Quote:
A convenience store currently stocks 48 bottles of mineral water.
The bottles have two sizes of either 20 or 40 ounces each. The average
volume per bottle the store currently has in stock is 35 ounces. How many 40
ounce bottles must be sold for the average volume per bottle to be reduced to 25
ounces if no 20 ounce bottles are sold?

Quote:
Hi,
the other method would be weighted average method.. people have already used it above, still ill do it once again..

TWO steps..

first - initial numbers
20 and 40 avail and average is 35..
so $$\frac{# of 20}{# of 40} = \frac{40-35}{35-20} = \frac{1}{3}$$
so # of 20 $$= \frac{1}{1+3} *48 =12$$..
and # of 40 ounces = 48-12 = 36

second -
20 and 40 avail and average is 25..
so$$\frac{# of 20}{# of 40} = \frac{40-25}{25-20} =\frac{3}{1}$$
so # of 20$$= \frac{3}{1+3} *x =12$$, here we know # of 20 ounces remains constant..
so x= 16
and # of 40 ounces = 16-12 = 4..
now # of 40 ounces bottle sold = 36-4 = 32

question stem says:if no 20 ounce bottles are sold, meaning no bottles are sold at all , not : additional bottles are not sold.
Are we on same page?
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Re: A convenience store currently stocks 48 bottles of mineral water. The  [#permalink]

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14 Apr 2018, 18:15
chetan2u Bunuel VeritasPrepKarishma niks18

Quote:
A convenience store currently stocks 48 bottles of mineral water.
The bottles have two sizes of either 20 or 40 ounces each. The average
volume per bottle the store currently has in stock is 35 ounces. How many 40
ounce bottles must be sold for the average volume per bottle to be reduced to 25
ounces if no 20 ounce bottles are sold?

Quote:
Hi,
the other method would be weighted average method.. people have already used it above, still ill do it once again..

TWO steps..

first - initial numbers
20 and 40 avail and average is 35..
so $$\frac{# of 20}{# of 40} = \frac{40-35}{35-20} = \frac{1}{3}$$
so # of 20 $$= \frac{1}{1+3} *48 =12$$..
and # of 40 ounces = 48-12 = 36

second -
20 and 40 avail and average is 25..
so$$\frac{# of 20}{# of 40} = \frac{40-25}{25-20} =\frac{3}{1}$$
so # of 20$$= \frac{3}{1+3} *x =12$$, here we know # of 20 ounces remains constant..
so x= 16
and # of 40 ounces = 16-12 = 4..
now # of 40 ounces bottle sold = 36-4 = 32

question stem says:if no 20 ounce bottles are sold, meaning no bottles are sold at all , not : additional bottles are not sold.
Are we on same page?

Yes you are right in your assessment that no new 20 ounce bottles are added or sold.

In the second part of the solution, "x" denotes the total number of bottles left after selling 40 ounce bottles. In this solution number of 20 ounce bottle remains 12. So on solving, we get x=16 i.e. only 16 bottles are left after 40 ounce bottles are sold. so out of 16, 12 are 20 ounce bottles and the remaining 4 are 40 ounce bottles. As there are 36, 40 ounce bottles, so 36-4=32, 40 ounce bottles were sold.
Intern
Joined: 30 Sep 2018
Posts: 20
Re: A convenience store currently stocks 48 bottles of mineral water. The  [#permalink]

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09 Oct 2019, 05:53
Hi Bunuel
It takes me ~3 mins to solve this one because of operations...could you suggest a method that takes < 2 mins?
Intern
Joined: 15 Sep 2019
Posts: 5
Re: A convenience store currently stocks 48 bottles of mineral water. The  [#permalink]

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15 Dec 2019, 09:44
ArvGMAT wrote:
32

Here is how I got it:

Average is 35 ounces
x is # of 20 ounce bottles
y is # of 40 ounce bottles

20x+40y/x+y = 35
solve to get y=3x

x+y=48 bottles
x=12, y=36

20x+40z/x+z=25

plug x=12 and solve for z, we get z = 4

So, y-z is # of bottles sold i.e 36-4 = 32

Thanks! I think it is the most fast and clear explanation!
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Re: A convenience store currently stocks 48 bottles of mineral water. The  [#permalink]

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15 Dec 2019, 10:05
dred wrote:
A convenience store currently stocks 48 bottles of mineral water. The bottles have two sizes of either 20 or 40 ounces each. The average volume per bottle the store currently has in stock is 35 ounces. How many 40 ounce bottles must be sold for the average volume per bottle to be reduced to 25 ounces if no 20 ounce bottles are sold?

(A) 10
(B) 20
(C) 30
(D) 32
(E) 34

Total bottles = 48
Present ratio of 20 to 40 ounces bottles to make average 35 ounces = 1:3
20 ounces bottles = 12
40 ounces bottles = 36

To make average 25 ounces , ratio of 20 to 40 ounces bottles = 3:1
Since no 20 ounces bottles are sold, number of 40 ounces bottles = 12/3 = 4

Number of 40 ounces bottles to be sold = 36-4 = 32 bottles

IMO D

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Re: A convenience store currently stocks 48 bottles of mineral water. The   [#permalink] 15 Dec 2019, 10:05

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