{"title":"Bartlett Correctability of Empirical Likelihood for Time Series","authors":"N. Chan, Li Liu","doi":"10.14490/JJSS.40.221","DOIUrl":"https://doi.org/10.14490/JJSS.40.221","url":null,"abstract":"A desirable feature of the empirical likelihood (EL) method is its Bartlett correctability. Previous studies have only demonstrated that the Bartlett correctability of EL for independent cases. This paper considers the Bartlett correctability of EL in time series models. The validity of the formal Edgeworth expansion for the EL ratio statistic in the short-memory case is established and through meticulous calculations, a closed form expansion for the statistic is deduced. The order of the coverage error of the EL confidence region for time series is obtained based on such an Edgeworth expansion of the EL ratio statistic. It is further demonstrated that the coverage error can be reduced by an order of magnitude after using a Bartlett correction. Finally, a simulation study is presented to illustrate the Bartlett correctability of EL in the short-memory case.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122508154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Empirical Likelihood Estimation for a Class of Stable Processes","authors":"Hiroaki Ogata","doi":"10.14490/JJSS.40.207","DOIUrl":"https://doi.org/10.14490/JJSS.40.207","url":null,"abstract":"We investigate the empirical likelihood estimation for a parameter of linear processes whose innovations have i.i.d. symmetric α-stable distributions. To construct the estimating function for the empirical likelihood method, we make use of the empirical and theoretical characteristic functions. The asymptotic normality of the maximum empirical likelihood estimator is derived. The behavior of the asymptotic variance with respect to infinitesimal perturbations of the dependence effect is studied and we find that it is dependence robust when α > 1. Numerical studies are also given.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"083 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129017994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Recent Developments of Threshold Estimation for Nonlinear Time Series","authors":"Ngai Hang, Y. Kutoyants","doi":"10.14490/JJSS.40.277","DOIUrl":"https://doi.org/10.14490/JJSS.40.277","url":null,"abstract":"In this article, several important problems of threshold estimation in a Bayesian framework for nonlinear time series models are discussed. The paper starts with the issue of calculating the maximum likelihood and the Bayesian estimators for threshold autoregressive models. It turns out that the asymptotic efficiency of the Bayesian estimators in this type of singular estimation problems is superior than the maximum likelihood estimators. To illustrate the properties of these estimators and to explain the proposed method, the paper begins with the study of a linear threshold autoregressive model with i.i.d. Gaussian noise. The paper then extends the idea to other nonlinear and non-Gaussian models and illustrates the paradigm of limiting likelihood ratio, which is applicable to a much wider class of nonlinear models. The article also investigates the robustness issue and the possibility of restricting the observation window by narrow bands, which allows one to obtain asymptotically efficient estimators. Finally, the paper indicates how these results can be generalized from a TAR(1) model to a higher-order TAR(p) model with multiple thresholds. The paper concludes with a discussion of other related problems and illustrates the methodology by numerical simulations.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132319422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Posterior Density for the Difference Between Two Binominal Proportions and the Highest Posterior Density Credible Interval","authors":"Youhei Kawasaki, E. Miyaoka","doi":"10.14490/JJSS.40.265","DOIUrl":"https://doi.org/10.14490/JJSS.40.265","url":null,"abstract":"The statistical inference concerning the difference between two independent binominal proportions has often been discussed in medical and statistical literature. This discussion is far more often based on the frequency theory of statistical inference than on the Bayesian theory. In this article, we propose the expression of the posterior probability density function (pdf) for the difference between two independent binominal proportions. In addition, we calculate the exact Highest Posterior Density (HPD) credible interval by using this expression. We also compare both the exact HPD credible interval and the approximate credible interval. We find that the former always has a narrower interval length than the latter.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122842925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"SHRINKAGE GMM ESTIMATION IN CONDITIONAL MOMENT RESTRICTION MODELS","authors":"R. Okui","doi":"10.14490/JJSS.39.239","DOIUrl":"https://doi.org/10.14490/JJSS.39.239","url":null,"abstract":"This paper proposes the shrinkage generalized method of moments estimator to address the “many moment conditions” problem in the estimation of conditional moment restriction models. This estimator is obtained as the minimizer of the function constructed by modifying the GMM objective function, such that we shrink the effect of a subset of moment conditions that are less important and used only for efficiency. We provide the closed form of the shrinkage parameter that minimizes the asymptotic mean squared error. A simulation study shows encouraging results.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125614609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Saddlepoint Approximation to the Limiting Distribution of a k -sample Baumgartner Statistic","authors":"H. Murakami, T. Kamakura, Midori Taniguchi","doi":"10.14490/JJSS.39.133","DOIUrl":"https://doi.org/10.14490/JJSS.39.133","url":null,"abstract":"Testing hypothesis is one of the most important problems in a nonparametric statistic. Various nonparametric test statistics have been proposed and discussed for a long time. We use the exact critical value for testing hypothesis when the sample sizes are small. However, for large sample sizes, it is very difficult to evaluate the exact critical value. Therefore, the limiting distributions of nonparametric tests are needed for testing the hypothesis. The purpose of this paper is to derive the limiting distribution of a k-sample Baumgartner test proposed by Murakami (2006). At first we consider a two-sample problem, which is one of the most common types of statistical problems. Let X = (X1, . . . , Xn) and Y = (Y1, . . . , Ym) be two random samples of size n and m independent observations, each of which has a continuous distribution described as F (x) and G(y), respectively. Let R1 < · · · < Rn and H1 < · · · < Hm denote the combined-samples ranks of the X-value and Y -value in increasing order of magnitude, respectively. One of the problems is to test the hypothesis H0 : F = G against H1 : not H0. Baumgartner et al. (1998) defined a novel nonparametric two-sample statistic for the hypothesis as","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134157206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ASYMPTOTIC EFFICIENCY OF ESTIMATING FUNCTION ESTIMATORS FOR NONLINEAR TIME SERIES MODELS","authors":"Tomoyuki Amano","doi":"10.14490/JJSS.39.209","DOIUrl":"https://doi.org/10.14490/JJSS.39.209","url":null,"abstract":"The conditional least squares (CLS) estimator proposed by Tjostheim (1986) is convenient and important for nonlinear time series models. However this convenient estimator is not generally asymptotically efficient. Hence Chandra and Taniguchi (2001) proposed a G estimator based on Godambe’s asymptotically optimal estimating function. For important nonlinear time series models, e.g., RCA, GARCH, nonlinear AR models, we show the asymptotic variance of the G estimator is smaller than that of the CLS estimator, and the G estimator is asymptotically efficient if the innovation is Gaussian. Numerical studies for the comparison of the asymptotic variance of the G estimator, that of the CLS estimator and the Fisher information are also given. They elucidate some interesting features of the G estimator.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"449 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122599712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Two Sample Problem for Rounded Data","authors":"Y. Nishiyama","doi":"10.14490/JJSS.39.233","DOIUrl":"https://doi.org/10.14490/JJSS.39.233","url":null,"abstract":"This paper deals with the two sample problem for rounded data in the i.i.d. model. It is well known that under the null hypothesis the two sample KolmogorovSmirnov statistic without rounding converges in distribution to the supremum of a standard Brownian bridge. We establish that a natural statistic of the KolmogorovSmirnov type based on the rounded data converges in distribution to the same limit as the full observation case. Our result is based on “Donsker’s theorem for discretized data” given by Nishiyama (2008, J. Japan Statist. Soc.).","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123368629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Saddlepoint Approximation to a Nonparametric Test for Ordered Alternatives","authors":"H. Murakami, T.H.M. Kawamura","doi":"10.14490/JJSS.39.143","DOIUrl":"https://doi.org/10.14490/JJSS.39.143","url":null,"abstract":"The approximation for the distribution function of a test statistic is extremely important in statistics. On testing the hypothesis in a multisample problem, the Jonckheere-Terpstra test is often used for testing the ordered location parameters. Herein, we performed a saddlepoint approximation with continuity correction in the upper tails for the Jonckheere-Terpstra statistic under finite sample sizes. We then compared the saddlepoint approximation with Odeh’s approximation to obtain the exact critical value. The table of critical values was extended by using the saddlepoint approximation. Additionally, the orders of errors of a saddlepoint approximation were derived.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123764171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"SYSTEMATIC APPROACH FOR PORTMANTEAU TESTS IN VIEW OF THE WHITTLE LIKELIHOOD RATIO","authors":"M. Taniguchi, Tomoyuki Amano","doi":"10.14490/JJSS.39.177","DOIUrl":"https://doi.org/10.14490/JJSS.39.177","url":null,"abstract":"Box and Pierce (1970) proposed a test statistic TBP which is the squared sum of m sample autocorrelations of the estimated residual process of an autoregressivemoving average model of order (p,q). TBP is called the classical portmanteau test. Under the null hypothesis that the autoregressive-moving average model of order (p,q) is adequate, they suggested that the distribution of TBP is approximated by a chi-square distribution with (m-p-q) degrees of freedom, “if m is moderately large”. This paper shows that TBP is understood to be a special form of the Whittle likelihood ratio test T PW for autoregressive-moving average spectral density with m-dependent residual processes. Then, it is shown that, for any finite m, T PW does not converge to a chi-square distribution with (m-p-q) degrees of freedom in distribution, and that if we assume Bloomfield’s exponential spectral density, T PW is asymptotically chisquare distributed for any finite m .F rom this observation we propose a modified T † PW which is asymptotically chi-square distributed. In view of the likelihood ratio, we also mention the asymptotics of a natural Whittle likelihood ratio test T WL R which is always asymptotically chi-square distributed. Its local power is also evaluated. Numerical studies illuminate interesting features of T PW , T † PW , and T WL R. Because many versions of the portmanteau test have been proposed and been used in a variety of fields, our systematic approach for portmanteau tests and proposal of tests will give another view and useful applications.","PeriodicalId":326924,"journal":{"name":"Journal of the Japan Statistical Society. Japanese issue","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121080007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}