Advertisement

Advances in Statistical Decision Theory and Applications

  • S. Panchapakesan
  • N. Balakrishnan

Part of the Statistics for Industry and Technology book series (SIT)

Table of contents

  1. Front Matter
    Pages i-l
  2. Bayesian Inference

  3. Decision Theory

    1. Front Matter
      Pages 97-97
    2. S. Ghosal, J. K. Ghosh, R. V. Ramamoorthi
      Pages 119-132
  4. Point and Interval Estimation—Classical Approach

    1. Front Matter
      Pages 133-133
    2. Raymond J. Carroll, L. A. Stefanski
      Pages 151-164
    3. Pranab K. Sen, Zhenwei Zhou
      Pages 165-178
    4. W. C. Kim, B. U. Park, K. H. Kang
      Pages 179-187
    5. Kathleen S. Fritsch, Jason C. Hsu
      Pages 189-204
  5. Tests of Hypotheses

    1. Front Matter
      Pages 205-205
    2. J. O. Berger, B. Boukai, Y. Wang
      Pages 207-223
  6. Ranking and Selection

  7. Distributions and Applications

  8. Industrial Applications

  9. Back Matter
    Pages 445-448

About this book

Introduction

Shanti S. Gupta has made pioneering contributions to ranking and selection theory; in particular, to subset selection theory. His list of publications and the numerous citations his publications have received over the last forty years will amply testify to this fact. Besides ranking and selection, his interests include order statistics and reliability theory. The first editor's association with Shanti Gupta goes back to 1965 when he came to Purdue to do his Ph.D. He has the good fortune of being a student, a colleague and a long-standing collaborator of Shanti Gupta. The second editor's association with Shanti Gupta began in 1978 when he started his research in the area of order statistics. During the past twenty years, he has collaborated with Shanti Gupta on several publications. We both feel that our lives have been enriched by our association with him. He has indeed been a friend, philosopher and guide to us.

Keywords

Derivation Finite Logistic Regression Mathematics Methodology Normal distribution Random variable Regression Variable Variance calculus correlation function model

Editors and affiliations

  • S. Panchapakesan
    • 1
  • N. Balakrishnan
    • 2
  1. 1.Department of MathSouthern Illinois UniversityCarbondaleUSA
  2. 2.Department of Mathematics and StatisticsMcMaster UniversityHamiltonCanada

Bibliographic information