The Art of Progressive Censoring : Applications to Reliability and Quality / by N. Balakrishnan, Erhard Cramer.

Format:

Book

Author/Creator:

Balakrishnan, N., Author.

Cramer, Erhard, Author.

Series:

Statistics for Industry and Technology, 2364-625X

Language:

English

Subjects (All):

Statistics.

Biometry.

Probabilities.

Mathematics.

Statistical Theory and Methods.

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

Biostatistics.

Probability Theory.

Applications of Mathematics.

Local Subjects:

Statistical Theory and Methods.

Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

Biostatistics.

Probability Theory.

Applications of Mathematics.

Physical Description:

1 online resource (652 pages) : illustrations, charts, graphs, tables.

Edition:

1st ed. 2014.

Place of Publication:

New York, NY : Springer New York : Imprint: Birkhäuser, 2014.

Language Note:

English

Summary:

This monograph offers a thorough and updated guide to the theory and methods of progressive censoring, an area that has experienced tremendous growth in recent years. Progressive censoring, originally proposed in the 1950s, is an efficient method of handling samples from industrial experiments involving lifetimes of units that have either failed or censored in a progressive fashion during the life test, with many practical applications to reliability and quality. Key topics and features: Data sets from the literature as well as newly simulated data sets are used to illustrate concepts throughout the text Emphasis on real-life applications to life testing, reliability, and quality control Discussion of parametric and nonparametric inference Coverage of experimental design with optimal progressive censoring The Art of Progressive Censoring is a valuable reference for graduate students, researchers, and practitioners inapplied statistics, quality control, life testing, and reliability. With its accessible style and concrete examples, the work may also be used as a textbook in advanced undergraduate or beginning graduate courses on censoring or progressive censoring, as well as a supplementary textbook for a course on ordered data.

Contents:

Part I: Distribution Theory and Models

Progressive censoring: Data and models

Progressive Type-II censoring: Distribution theory

Further distributional results on progressive Type-II censoring

Progressive Type-I censoring: Basic properties

Progressive hybrid censoring: Distributions and properties

Adaptive progressive Type-II censoring and related models

Moments of progressively Type-II censored order statistics

Simulation of progressively censored order statistics

Information Measures

Progressive Type-II censoring under non-standard conditions

Part II: Inference

Linear estimation in progressive Type-II censoring

Maximum likelihood estimation in progressive Type-II censoring

Point estimation in progressive Type-I censoring

Progressive hybrid and adaptive censoring and related inference

Bayesian inference for progressively Type-II censored data

Point prediction from progressively Type-II censored samples

Statistical intervals for progressively Type-IIcensored data

Progressive Type-I interval censored data

Goodness-of-fit-tests in progressive Type-II censoring

Counting and quantile processes and progressive censoring

Nonparametric inferential issues in progressive Type-II censoring

Part III: Applications in Survival Analysis and Reliability

Acceptance sampling plans

Accelerated life-testing

Stress-strength models with progressively censored data

Multi-sample models

Optimal experimental designs

Part IV: Appendices

Appendix A: Distributions

Appendix B: Additional demonstrative datasets

Notation

References

Author index

Subject index.

Notes:

Bibliographic Level Mode of Issuance: Monograph

Includes bibliographical references and index.

ISBN:

0-8176-4807-0