Progressive Censoring

Theory, Methods, and Applications

AvN. Balakrishnan,Rita Aggarwala

Inbunden, Engelska, 2000

Del i serien Statistics for Industry and Technology

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Beskrivning

This new volume offers a throughout 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). This book first introduces progressive sampling foundations, then discusses various properties of progressive samples. It also describes how to make exact or approximate inferences for the difference statistical models with samples based on progressive censoring schemes. With many concrete examples, the book points out the greater efficiency gained by suing this scheme instead of classical right-censorship methods. With its accessible style and examples, the book should be an essential resource for progressive censoring methodology.Advanced students, practitioners, and professionals in applied statistics, reliability and life-testing research should find it a useful guide to understanding and using this new methodology in their work.

Produktinformation

Utgivningsdatum:2000-06-16
Mått:178 x 254 x 21 mm
Vikt:707 g
Format:Inbunden
Språk:Engelska
Serie:Statistics for Industry and Technology
Antal sidor:248
Upplaga:2000
Förlag:Birkhauser Boston Inc
ISBN:9780817640019

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Innehållsförteckning

1 Introduction.- 1.1 The Big Picture.- 1.2 Genesis.- 1.3 The Need for Progressive Censoring.- 1.4 A Relatively Unexplored Idea.- 1.5 Mathematical Notations.- 1.6 A Friendly Note.- 2 Mathematical Properties of Progressively Type-II Right Censored Order Statistics.- 2.1 General Continuous Distributions.- 2.2 The Exponential Distribution: Spacings.- 2.3 The Uniform Distribution: Ratios.- 2.4 The Pareto Distribution: Ratios.- 2.5 Bounds for Means and Variances.- 3 Simulational Algorithms.- 3.1 Introduction.- 3.2 Simulation Using the Uniform Distribution.- 3.3 Simulation Using the Exponential Distribution.- 3.4 General Progressively Type-II Censored Samples.- 4 Recursive Computation and Algorithms.- 4.1 Introduction.- 4.2 The Exponential Distribution.- 4.3 The Doubly Truncated Exponential Distribution.- 4.4 The Pareto Distribution and Truncated Forms.- 4.5 The Power Function Distribution and Truncated Forms.- 5 Alternative Computational Methods.- 5.1 Introduction.- 5.2 Formulas in Terms of Moments of Usual Order Statistics.- 5.3 Formulas in the Case of Symmetric Distributions.- 5.4 Other Relations for Moments.- 5.5 First-Order Approximations to the Moments.- 6 Linear Inference.- 6.1 One-Parameter (Scale) Models.- 6.2 Two-Parameter (Location-Scale) Models.- 6.3 Best Linear Invariant Estimation.- 7 Likelihood Inference: Type-I and Type-II Censoring.- 71. Introduction.- 7.2 General Continuous Distributions.- 7.3 Specific Continuous Distributions.- 8 Linear Prediction.- 8.1 Introduction.- 8.2 The Exponential Case.- 8.3 Case of General Distributions.- 8.4 A Simple Approach Based on BLUEs.- 8.5 First-Order Approximations to BLUPs.- 8.6 Prediction Intervals.- 8.7 Illustrative Examples.- 9 Conditional Inference.- 9.1 Introduction.- 9.2 Inference for Location and Scale Parameters.- 9.3 Inference for Quantiles and Reliability and Prediction Intervals.- 9.4 Results for Extreme Value Distribution.- 9.5 Results for Exponential Distribution.- 9.6 Illustrative Examples.- 9.7 Results for Pareto Distribution.- 10 Optimal Censoring Schemes.- 10.1 Introduction.- 10.2 The Exponential Distribution.- 10.3 The Normal Distribution.- 10.4 The Extreme Value Distribution.- 10.5 The Extreme Value (II) Distribution.- 10.6 The Log-Normal Distribution.- 10.7 Tables.- 11 Acceptance Sampling Plans.- 11.1 Introduction.- 11.2 The Exponential Distribution.- 11.3 The Log-Normal Distribution.- Author Index.