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© 2000

Progressive Censoring

Theory, Methods, and Applications

Book

Part of the Statistics for Industry and Technology book series (SIT)

Table of contents

  1. Front Matter
    Pages i-xv
  2. N. Balakrishnan, Rita Aggarwala
    Pages 1-10
  3. N. Balakrishnan, Rita Aggarwala
    Pages 31-40
  4. N. Balakrishnan, Rita Aggarwala
    Pages 41-65
  5. N. Balakrishnan, Rita Aggarwala
    Pages 67-83
  6. N. Balakrishnan, Rita Aggarwala
    Pages 85-115
  7. N. Balakrishnan, Rita Aggarwala
    Pages 117-138
  8. N. Balakrishnan, Rita Aggarwala
    Pages 139-165
  9. N. Balakrishnan, Rita Aggarwala
    Pages 167-181
  10. N. Balakrishnan, Rita Aggarwala
    Pages 183-214
  11. N. Balakrishnan, Rita Aggarwala
    Pages 215-222
  12. Back Matter
    Pages 223-248

About this book

Introduction

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 At the time of the first failure, Rl of the n - 1 surviving units are randomly withdrawn (or censored) from the life-testing experiment.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).

Keywords

Censoring Likelihood Norm Normal distribution Simulation Variance censored samples life testing progressive censoring quality quality control reliability testing statistics

Authors and affiliations

  1. 1.Department of Mathematics and StatisticsMcMaster UniversityHamiltonCanada
  2. 2.Department of Mathematics and StatisticsUniversity of CalgaryCalgaryCanada

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