Progressive Censoring : Theory, Methods, and Applications

N. Balakrishnan

ISBN 10: 0817640010 / ISBN 13: 9780817640019

Published by Birkhauser Boston Jun 2000, 2000

About this Item

Neuware - 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.

Seller Inventory # 9780817640019

Bibliographic Details

• Title: Progressive Censoring : Theory, Methods, and Applications
• Publisher: Birkhauser Boston Jun 2000
• Publication Date: 2000
• Language: English
• ISBN 10: 0817640010
• ISBN 13: 9780817640019
• Binding: Buch
• Condition: Neu
• Dimensions: 260W x 183H x 21D millimeters 260 millimeters width by 183 millimeters height by 21 millimeters depth
• Weight: 707 grams

About this title

Synopsis

Censored sampling arises in a life-testing experiment whenever the experimenter does not observe (either intentionally or unintentionally) the failure times of all units placed on a life-test. Inference based on censored sampling has been studied during the past 50 years by numerous authors for a wide range of lifetime distributions such as normal, exponential, gamma, Rayleigh, Weibull, extreme value, log-normal, inverse Gaussian, logistic, Laplace, and Pareto. Naturally, there are many different forms of censoring that have been discussed in the literature. In this book, we consider a versatile scheme of censoring called progressive Type-II censoring. Under this scheme of censoring, from a total of n units placed on a life-test, only m are completely observed until failure. At the time of the first failure, Rl of the n - 1 surviving units are randomly withdrawn (or censored) from the life-testing experiment. At the time of the next failure, R2 of the n - 2 -Rl surviving units are censored, and so on. Finally, at the time of the m-th failure, all the remaining Rm = n - m -Rl - . . . - Rm-l surviving units are censored. Note that censoring takes place here progressively in m stages. Clearly, this scheme includes as special cases the complete sample situation (when m = nand Rl = . . . = Rm = 0) and the conventional Type-II right censoring situation (when Rl = . . . = Rm-l = 0 and Rm = n - m).