Statistics for Industry and Technology : Theory, Methods, and Applications - N. Balakrishnan

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Statistics for Industry and Technology

Theory, Methods, and Applications

By: N. Balakrishnan, Rita Aggarwala

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Hardcover | 16 June 2000

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Hardcover
268 Pages

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25.4 x 17.78 x 1.91

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This new book offers a thorough guide to the theory and methods of progressive censoring for practitioners and professionals in applied statistics, quality control, life testing and reliability testing. In many industrial experiments involving lifetimes of machines or units, experiments have to be terminated early due to a variety of circumstances. Samples that arise from such experiments are called censored samples, and a new, efficient alternative method is referred to as "progressive censoring" (where the removal of live units at time of failure is employed).

Progressive Censoring first introduces progressive sampling foundations, then discusses various properties of progressive samples. It also describes how to make exact or approximate inferences for the different statistical models with samples based on progressive censoring schemes. With many concrete examples, the book points out the greater efficiency gained by using this scheme instead of classical right-censoring methods.

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Preface
List of Tables
Introduction	p. 1
Mathematical Properties of Progressively Type-II Right Censored Order Statistics	p. 11
General Continuous Distributions	p. 11
The Exponential Distribution: Spacings	p. 16
The Uniform Distribution: Ratios	p. 20
The Pareto Distribution: Ratios	p. 23
Bounds for Means and Variances	p. 26
Simulational Algorithms	p. 31
Simulation Using the Uniform Distribution	p. 32
Simulation Using the Exponential Distribution	p. 33
General Progressively Type-II Censored Samples	p. 34
Recursive Computation and Algorithms	p. 41
The Exponential Distribution	p. 41
The Doubly Truncated Exponential Distribution	p. 50
The Pareto Distribution and Truncated Forms	p. 57
The Power Function Distribution and Truncated Forms	p. 62
Alternative Computational Methods	p. 67
Formulas in Terms of Moments of Usual Order Statistics	p. 67
Formulas in the Case of Symmetric Distributions	p. 69
Other Relations for Moments	p. 78
First-Order Approximations to the Moments	p. 81
Linear Inference	p. 85
One-Parameter (Scale) Models	p. 85
Two-Parameter (Location-Scale) Models	p. 96
Best Linear Invariant Estimation	p. 112
Likelihood Inference: Type-I and Type-II Censoring	p. 117
General Continuous Distributions	p. 118
Specific Continuous Distributions	p. 120
Linear Prediction	p. 139
The Exponential Case	p. 139
Case of General Distributions	p. 144
A Simple Approach Based on BLUEs	p. 150
First-Order Approximations to BLUPs	p. 154
Prediction Intervals	p. 157
Illustrative Examples	p. 159
Conditional Inference	p. 167
Inference for Location and Scale Parameters	p. 167
Inference for Quantiles and Reliability and Prediction Intervals	p. 169
Results for Extreme Value Distribution	p. 172
Results for Exponential Distribution	p. 173
Illustrative Examples	p. 175
Results for Pareto Distribution	p. 178
Optimal Censoring Schemes	p. 183
The Exponential Distribution	p. 186
The Normal Distribution	p. 187
The Extreme Value Distribution	p. 190
The Extreme Value (II) Distribution	p. 192
The Log-Normal Distribution	p. 193
Tables	p. 195
Acceptance Sampling Plans	p. 215
The Exponential Distribution	p. 215
The Log-Normal Distribution	p. 220
Bibliography	p. 223
Author Index	p. 235
Subject Index	p. 239
Table of Contents provided by Blackwell. All Rights Reserved.

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