Name: Advances in Statistical Decision Theory and Applications
ISBN: 978-1-4612-2308-5

Overview

Editors:

S. Panchapakesan⁰,
N. Balakrishnan¹

S. Panchapakesan
1. Department of Math, Southern Illinois University, Carbondale, USA
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N. Balakrishnan
1. Department of Mathematics and Statistics, McMaster University, Hamilton, Canada
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Part of the book series: Statistics for Industry and Technology (SIT)

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Table of contents (28 chapters)

Tests of Hypotheses
1. The Large Deviation Principle for Common Statistical Tests Against a Contaminated Normal
  
  N. Rao Chaganty, J. Sethuraman
  
  Pages 239-252
2. Multiple Decision Procedures for Testing Homogeneity of Normal Means With Unequal Unknown Variances
  
  Deng-Yuan Huang, Ching-Ching Lin
  
  Pages 253-262
Ranking and Selection
1. Front Matter
  
  Pages 263-263
  
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2. A Sequential Multinomial Selection Procedure With Elimination
  
  D. M. Goldsman, A. J. Hayter, T. M. Kastner
  
  Pages 265-275
3. An Integrated Formulation for Selecting the Best From Several Normal Populations in Terms of the Absolute Values of Their Means: Common Known Variance Case
  
  S. Jeyaratnam, S. Panchapakesan
  
  Pages 277-289
4. Applications of Two Majorization Inequalities to Ranking and Selection Problems
  
  Y. L. Tong
  
  Pages 291-301
Distributions and Applications
1. Front Matter
  
  Pages 303-303
  
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2. Correlation Analysis of Ordered Observations From a Block-Equicorrelated Multivariate Normal Distribution
  
  Marlos Viana, Ingram Olkin
  
  Pages 305-322
3. On Distributions With Periodic Failure Rate and Related Inference Problems
  
  B. L. S. Prakasa Rao
  
  Pages 323-341
4. Venn Diagrams, Coupon Collections, Bingo Games and Dirichlet Distributions
  
  Milton Sobel, Krzysztof Frankowski
  
  Pages 343-367
Industrial Applications
1. Front Matter
  
  Pages 369-369
  
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2. Control Charts for Autocorrelated Process Data
  
  Ajit C. Tamhane, Edward C. Malthouse
  
  Pages 371-385
3. Reconstructive Estimation in a Parametric Random Censorship Model With Incomplete Data
  
  Tommaso Gastaldi
  
  Pages 387-404
4. A Review of the Gupta-Sobel Subset Selection Rule for Binomial Populations With Industrial Applications
  
  Gary C. McDonald, W. Craig Palmer
  
  Pages 405-416
5. The Use of Subset Selection in Combined-Array Experiments to Determine Optimal Product or Process Designs
  
  Thomas Santner, Guohua Pan
  
  Pages 417-430
6. Large-Sample Approximations to the Best Linear Unbiased Estimation and Best Linear Unbiased Prediction Based on Progressively Censored Samples and Some Applications
  
  N. Balakrishnan, C. R. Rao
  
  Pages 431-444
Back Matter

Pages 445-448

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Keywords

About this book

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.

Editors and Affiliations

Department of Math, Southern Illinois University, Carbondale, USA

S. Panchapakesan
Department of Mathematics and Statistics, McMaster University, Hamilton, Canada

N. Balakrishnan

Bibliographic Information

Book Title: Advances in Statistical Decision Theory and Applications
Editors: S. Panchapakesan, N. Balakrishnan
Series Title: Statistics for Industry and Technology
DOI: https://doi.org/10.1007/978-1-4612-2308-5
Publisher: Birkhäuser Boston, MA
eBook Packages: Springer Book Archive
Hardcover ISBN: 978-0-8176-3965-5Due: 23 September 1997
Softcover ISBN: 978-1-4612-7495-7Published: 15 September 2011
eBook ISBN: 978-1-4612-2308-5Published: 06 December 2012
Series ISSN: 2364-6241
Series E-ISSN: 2364-625X
Edition Number: 1
Number of Pages: 498
Topics: Probability Theory and Stochastic Processes, Applications of Mathematics
Industry Sectors: Aerospace, Biotechnology, Consumer Packaged Goods, Electronics, Energy, Utilities & Environment, Finance, Business & Banking, IT & Software, Pharma, Telecommunications

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Advances in Statistical Decision Theory and Applications

Overview

Access this book

Other ways to access

Table of contents (28 chapters)

Tests of Hypotheses

Ranking and Selection

Front Matter

Distributions and Applications

Front Matter

Industrial Applications

Front Matter

Back Matter

Keywords

About this book

Editors and Affiliations

Department of Math, Southern Illinois University, Carbondale, USA

Department of Mathematics and Statistics, McMaster University, Hamilton, Canada

Bibliographic Information

Publish with us

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