Institute of Mathematical Statistics Collections

Beyond Parametrics in Interdisciplinary Research: Festschrift in Honor of Professor Pranab K. Sen

Editor: N. Balakrishnan
Editor: Edsel A. Peña
Editor: Mervyn J. Silvapulle

Collections, Volume 1
Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2008.
407 pp.

Abstract:

Pranab K. Sen has contributed extensively to many areas of Statistics including order statistics, nonparametrics, robust inference, sequential methods, asymptotics, biostatistics, clinical trials, bioenvironmental studies and bioinformatics. His long list of over 600 publications and 22 books and volumes along with numerous citations during the past 5 decades bear testimony to his work.

All three of us have had the good fortune of being associated with him in different capacities. He has given professional and personal advice on many occasions to all of us, and we feel that our lives have certainly been enriched by our association with him. He has been over the years a friend, philosopher and a guide to us, and still continues to be one!

While parametric statistical inference remains ever so popular, semi-parametric, Bayesian and nonparametric inferential methods have attracted great attention from numerous applied scientists because of their weaker assumptions, which make them naturally robust and so more appropriate in real-life applications. This clearly signals for “beyond parametrics” approaches which include nonparametrics, semi-parametrics, Bayes methods and many others. Motivated by this feature, and his drive in the “beyond parametrics” area, we thought that it will be only appropriate for a volume in honor of Pranab Kumar Sen to focus on this aspect of statistical inference and its applications. With this in mind, we have put together this volume in order to (i) review some of the recent developments in this direction, (ii) focus on some new methodologies and highlight their applications, and (iii) suggest some interesting open problems and possible new directions for further research.

With these specific goals in mind, we invited a number of authors to contribute an article for this volume. These authors are not only experts in parametric, semi-parametric, Bayesian and nonparametric inferential methods, but also form a representative group from former students, colleagues, long-time friends, and other close professional associates of Pranab Kumar Sen. All the articles received have been properly peer reviewed according to the conditions set forth by the IMS Lecture Notes Editor.

It is important to mention here that this volume is not a proceedings, but rather a carefully planned volume consisting of articles that are consistent with the goal of highlighting developments “beyond parametric inference” and their applications.

Our sincere thanks to Professor Sen for having given his consent to this venture and his advice on organisational matters whenever we asked. Next, our special thanks go to all the authors who have contributed to this volume. All these authors share our respect and admiration for the various contributions and accomplishments of Pranab Kumar Sen and provided great cooperation during the entire course of this project. We express our gratitude to Professors Rick Vitale and Anthony Davison, the Past and Present Editors of the IMS Lecture Notes, for lending their support to this project and also for providing constant encouragement and help during the preparation of this volume.

We would like to thank the numerous reviewers for helping us with the reviews of papers, Dr. Vytas Statulevičius for prompt assistance related to to LaTeX, Ms Geri Mattson for carrying out the publications related tasks expeditiously and efficiently, and Ms Mala Raghavan and Mr Kulan Ranasinghe for editorial assistance. We enjoyed immensely putting this volume together, and it is with great pleasure that we dedicate it to Pranab Kumar Sen!

Permanent link to this monograph: http://projecteuclid.org/euclid.imsc/1207058254
ISBN:978-0-940600-73-7
ISBN:0-940600-73-0

Copyright © 2008, Institute of Mathematical Statistics.

Title and Copyright Pages

i-ii

Table of Contents

iii-iv

Preface

v-vi

Contributor's List

vii-viii

Picture

ix

Pranab Kumar Sen: Life and works

N. Balakrishnan, Edsel A. Peña, and Mervyn J. Silvapulle; 1-16

Analytic perturbations and systematic bias in statistical modeling and inference

Jerzy A. Filar, Irene Hudson, Thomas Mathew, and Bimal Sinha; 17-34

Smooth estimation of mean residual life under random censoring

Yogendra P. Chaubey, and Arusharka Sen; 35-49

Order restricted inference for comparing the cumulative incidence of a competing risk over several populations

Hammou El Barmi, Subhash Kochar, and Hari Mukerjee; 50-61

Statistical inference under order restrictions on both rows and columns of a matrix, with an application in toxicology

Eric Teoh, Abraham Nyska, Uri Wormser, and Shyamal D. Peddada; 62-77

On the structure of a family of probability generating functions induced by shock models

Satrajit Roychoudhury, and Manish C. Bhattacharjee; 78-88

A Bayesian test for excess zeros in a zero-inflated power series distribution

Archan Bhattacharya, Bertrand S. Clarke, and Gauri S. Datta; 89-104

Posterior consistency of Dirichlet mixtures of beta densities in estimating positive false discovery rates

Subhashis Ghosal, Anindya Roy, and Yongqiang Tang; 105-115

Robust estimation in finite population sampling

Malay Ghosh; 116-122

Estimation of population-level summaries in general semiparametric repeated measures regression models

Arnab Maity, Tatiyana V. Apanasovich, and Raymond J. Carroll; 123-137

Smoothing-inspired lack-of-fit tests based on ranks

Jeffrey D. Hart; 138-155

A nonparametric control chart based on the Mann-Whitney statistic

Subhabrata Chakraborti, and Mark A. van de Wiel; 156-172

Regression rank scores in nonlinear models

Jana Jurečková; 173-183

Chernoff-Savage and Hodges-Lehmann results for Wilks’ test of multivariate independence

Marc Hallin, and Davy Paindaveine; 184-196

U-tests for variance components in one-way random effects models

Juvêncio S. Nobre, Julio M. Singer, and Mervyn J. Silvapulle; 197-210

A comparison of the Benjamini-Hochberg procedure with some Bayesian rules for multiple testing

Małgorzata Bogdan, Jayanta K. Ghosh, and Surya T. Tokdar; 211-230

On the Simes inequality and its generalization

Sanat K. Sarkar; 231-242

Multiple testing procedures under confounding

Debashis Ghosh; 243-256

A pattern mixture model for a paired 2 × 2 crossover design

Laura J. Simon, and Vernon M. Chinchilli; 257-271

Projected likelihood contrasts for testing homogeneity in finite mixture models with nuisance parameters

Debapriya Sengupta, and Rahul Mazumder; 272-281

Bootstrapping the Grenander estimator

Michael R. Kosorok; 282-292

Ratio tests for change point detection

Lajos Horváth, Zsuzsanna Horváth, and Marie Hušková; 293-304

On estimating the change point in generalized linear models

Kung-Yee Liang, and Hongling Zhou; 305-320

Using statistical smoothing to date medieval manuscripts

Andrey Feuerverger, Peter Hall, Gelila Tilahun, and Michael Gervers; 321-331

Sequential nonparametrics and semiparametrics: Theory, implementation and applications to clinical trials

Tze Leung Lai, and Zheng Su; 332-349

Estimating medical costs from a transition model

Joseph C. Gardiner, Lin Liu, and Zhehui Luo; 350-363

Correcting for selection bias via cross-validation in the classification of microarray data

J. Chevelu, G. J. McLachlan, and J. Zhu; 364-376

An asymptotically normal test for the selective neutrality hypothesis

Aluísio Pinheiro, Hildete P. Pinheiro, and Samara Kiihl; 377-389

Model selection and sensitivity analysis for sequence pattern models

Mayetri Gupta; 390-407

Institute of Mathematical Statistics Collections

Institute of Mathematical Statistics Collections