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.
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!
Copyright © 2008, Institute of Mathematical Statistics.
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
Estimation of population-level summaries in general semiparametric repeated measures regression models
Arnab Maity, Tatiyana V. Apanasovich, and Raymond J. Carroll; 123-137
A nonparametric control chart based on the Mann-Whitney statistic
Subhabrata Chakraborti, and Mark A. van de Wiel; 156-172
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
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
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