Contemporary developments in statistical theory sengupta ashis lahiri soumendra schick anton sriram t n
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Professor Hira Koul received his Ph. Applicability of these estimators and related bootstrap inference are illustrated using a real life data set. Synopsis This volume highlights Prof. Therefore, under the null hypothesis of any short memory processes, our new test statistic has a known asymptotic distribution. Hira Koul's achievements in many areas of Statistics, including Asymptotic theory of statistical inference, Robustness, Weighted empirical processes and their applications, Survival Analysis, Nonlinear time series and Econometrics, among others.

After providing a brief review of the existing literature, we introduce a class of novel estimators for this problem. Using penalized splines method, we are able to eliminate the effects of nuisance parameters typically induced by short memory autocorrelation. . Journal of Statistical Theory and Practice, 9, 345-418. Estimation of bivariate survival function for right censored data has a long history. For a family of two-sided truncated location distributions, based on the generalized Neyman—Pearson lemma, an upper bound for the asymptotic distributions of the absolute deviations of all asymptotically median unbiased estimators for the location parameter is established, upon which the asymptotic efficiency is defined. We discuss several examples and illustrate the results with simulations.

He has the unique distinction of being the first doctoral student of Professor Bickel. A one-year path in likelihood conception and the idea of random procedures, taught at Princeton collage to undergraduate and graduate scholars, varieties the center of this publication. Contemporary Developments in Statistical Theory: A Festschrift for Hira Lal Koul. The asymptotic theory is formally established using new weak convergence theorems for function-parametric processes. An adaptive asymptotically weak admissible median unbiased estimator of the location parameter is also constructed. The proposed test statistics are continuous functionals of a Khmaladze-Rossenblatt. Chapters are all unique papers that discover the frontiers of those components and should help researchers and graduate scholars operating in facts, Econometrics and similar components.

His distinguished career in Statistics includes the receipt of many prestigious awards, including the Senior Humbolt award 1995 , and dedicated service to the profession through editorial work for journals and through leadership roles in professional societies, notably as the past president of the International Indian Statistical Association. This covers the usual model as a special case. Recent developments in convex optimization are exploited to expand the applicability of the Kiefer-Wolfowitz nonparametric maximum likelihood estimator for mixture models. This approach has been widely employed by several authors in studying the asymptotic properties of tests of composite hyptheses, and has been a particularly powerful tool for deriving limit laws of goodness-of-fit tests. We provide numerical evidence of the superiority of our estimators over existing estimators. His distinctive profession in facts comprises the receipt of many prestigious awards, together with the Senior Humbolt award 1995 , and committed provider to the career via editorial paintings for journals and during management roles in expert societies, particularly because the earlier president of the foreign Indian Statistical organization.

Chapters are all original papers that explore the frontiers of these areas and will assist researchers and graduate students working in Statistics, Econometrics and related areas. For right censored failure time data, the proposed algorithm combines the Kaplan—Meier estimator for the susceptible proportion and weighted least square estimators for the multiple change-points and other model parameters. In this article, point estimates, point-wise confidence intervals and simultaneous confidence intervals of the two ratios are established under a semiparametric model that can be used in a sufficiently wide range of applications. We show that splines of degree four and higher satisfy those conditions and conduct a simulation study to evaluate quality of the fiducial estimates compared to the competing Bayesian solution. In this article, we study risks and Bayes risks of general thresholding estimates. Some ensuing problems of profile likelihood are also addressed. Hira Koul has graduated on the subject of 30 Ph.

We apply this to some well-known datasets and can identify outliers which would not have been detected using least squares. Sriram, Contemporary Developments in Statistical Theory A Festschrift for Hira Lal Koul , Springer International Publishing : Switzerland 2014, p. His research interests include Nonparametric Statistics, Time Series, Spatial Statistics, and Statistical inference for high dimensional data. At around the same time, he also developed the theory of weighted empirical processes which played a fundamental role in the study of asymptotic distribution of robust estimators e. We consider two popular nonparametric models describing measurements obtained from low and high angular resolution diffusion tensor imaging.

The finite-sample properties of our procedure are compared to other well-known tests in the literature. This yields a practical guideline on how to choose the number of gradient directions and the number of repetitions for estimation problems in this imaging context. Since the convergence of our test statistic toward its asymptotic distribution is relatively slow, Monte Carlo methods are investigated to determine the corresponding critical value. The long list of his distinguished collaborators is represented by the contributors to this volume. He is a Member of the Project Advisory Committee - Math. It is interesting in itself and allows, although not too easily, an explicit form of the limiting infinitely divisible distribution function. Results from a simulation study are also presented.

In: Soumendra Lahiri, Anton Schick, Ashis SenGupta, T. The failure probability ratio and the ratio of cumulative hazards are two measures that relate to the survival experience and supplement the hazard ratio in helping assess the treatment effect. Hira Koul's achievements in many areas of Statistics, including Asymptotic theory of statistical inference, Robustness, Weighted empirical processes and their applications, Survival Analysis, Nonlinear time series and Econometrics, among others. He served as an Editor of Sankhya, Series A 2007-2009 and currently, he is on the editorial boards of the Annals of Statistics and the Journal of Statistical Planning and Inference. In this chapter, we describe efficient estimators of parameters of the quantile regression function for general conditional constraints and for examples of more specific constraints. The heteroscedastic error and stationary densities of the two independent strong mixing strictly stationary time series can be possibly different.

The balance between the number of distinct directions for measurements and the number of repetitions is investigated from the statistical point of view. This article proposes asymptotic distribution-free speci. Estimation after selection from gamma populations with unequal known shape parameters. Then, we propose a new change-point detection algorithm in multiple change-point hazard regression models for fitting failure times that allows the existence of both susceptibles and long-term survivors. In addition, we assume that auxiliary information is available in the form of a conditional constraint. Somewhat surprisingly, the empirical characteristic function can provide the basis for selecting a transformation to achieve near symmetry. For clinical trials with time-to-event data, statistical inference often employs the constant hazard ratio assumption.

Thus, our results extend those of Koul and Stute 1999 and Khmaladze and Koul 2004 to the multivariate time-series heteroskedastic case. We discuss efficient estimation in quantile regression models where the quantile regression function is modeled parametrically. Non-uniform approximations for sums of discrete m-dependent random variables. Document type Contribution à ouvrage collectif Book Chapter — Chapitre Access type Accès restreint Publication date 2014 Language Anglais Host document Soumendra Lahiri, Anton Schick, Ashis SenGupta, T. This is, for example, the case if the mean regression function or the variance function can be modeled parametrically, e. Hira Koul used to be the 1st Ph.