Advances in Statistical Decision Theory and Applications

Advances in Statistical Decision Theory and Applications edited by S. Panchapakesan, N. Balakrishnan.

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, h...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Panchapakesan, S. (Editor), Balakrishnan, N. (Editor)
Format: eBook
Language:English
Published: Boston, MA : Birkhäuser Boston : Imprint: Birkhäuser, 1997.
Edition:1st ed. 1997.
Series:Statistics for Industry and Technology,
Springer eBook Collection.
Subjects:
Probabilities.
Applied mathematics.
Engineering mathematics.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • I: Bayesian Inference
  • 1 Bayes for Beginners? Some Pedagogical Questions
  • 2 Normal Means Revisited
  • 3 Bayes m-Truncated Sampling Allocations for Selecting the Best Bernoulli Population
  • 4 On Hierarchical Bayesian Estimation and Selection for Multivariate Hypergeometric Distributions
  • 5 Convergence Rates of Empirical Bayes Estimation and Selection for Exponential Populations With Location Parameters
  • 6 Empirical Bayes Rules for Selecting the Best Uniform Populations
  • II: Decision Theory
  • 7 Adaptive Multiple Decision Procedures for Exponential Families
  • 8 Non-Informative Priors Via Sieves and Packing Numbers
  • III: Point And Interval Estimation—Classical Approach
  • 9 From Neyman’s Frequentism to the Frequency Validity in the Conditional Inference
  • 10 Asymptotic Theory for the Simex Estimator in Measurement Error Models
  • 11 A Change Point Problem for Some Conditional Functionals
  • 12 On Bias Reduction Methods in Nonparametric Regression Estimation
  • 13 Multiple Comparisons With the Mean
  • IV: Tests Of Hypotheses
  • 14 Properties of Unified Bayesian-Frequentist Tests
  • 15 Likelihood Ratio Tests and Intersection-Union Tests
  • 16 The Large Deviation Principle for Common Statistical Tests Against a Contaminated Normal
  • 17 Multiple Decision Procedures for Testing Homogeneity of Normal Means With Unequal Unknown Variances
  • V: Ranking and Selection
  • 18 A Sequential Multinomial Selection Procedure With Elimination
  • 19 An Integrated Formulation for Selecting the Best From Several Normal Populations in Terms of the Absolute Values of Their Means: Common Known Variance Case
  • 20 Applications of Two Majorization Inequalities to Ranking and Selection Problems
  • VI: Distributions AND Applications
  • 21 Correlation Analysis of Ordered Observations From a Block-Equicorrelated Multivariate Normal Distribution
  • 22 On Distributions With Periodic Failure Rate and Related Inference Problems
  • 23 Venn Diagrams, Coupon Collections, Bingo Games and Dirichlet Distributions
  • VII: Industrial Applications
  • 24 Control Charts for Autocorrelated Process Data
  • 25 Reconstructive Estimation in a Parametric Random Censorship Model With Incomplete Data
  • 26 A Review of the Gupta-Sobel Subset Selection Rule for Binomial Populations With Industrial Applications
  • 27 The Use of Subset Selection in Combined-Array Experiments to Determine Optimal Product or Process Designs
  • 28 Large-Sample Approximations to Best Linear Unbiased Estimation and Best Linear Unbiased Prediction Based on Progressively Censored Samples and Some Applications.

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