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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 textEmphasis on real-life applications to life testing, reliability, and quality controlDiscussion of parametric and nonparametric inferenceCoverage of experimental design with optimal progressive censoring
The Art of Progressive Censoring is a valuable reference for graduate students, researchers, and practitioners in applied 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.
Front Matter
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 Nonstandard Conditions
Front Matter
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-II Censored Data
Progressive Type-I Interval Censored Data
Goodness-of-Fit Tests in Progressive Type-II Censoring
Counting and Quantile Processes and Progressive Censoring
Front Matter
Nonparametric Inferential Issues in Progressive Type-II Censoring
Front Matter
Acceptance Sampling Plans
Accelerated Life Testing
Stress–Strength Models with Progressively Censored Data
Multi-sample Models
Optimal Experimental Designs
Back Matter