Progressive Censoring

1. Front Matter

   Pages i-xv

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2. Introduction

   • N. Balakrishnan, Rita Aggarwala

   Pages 1-10

3. Mathematical Properties of Progressively Type-II Right Censored Order Statistics

   • N. Balakrishnan, Rita Aggarwala

   Pages 11-29

4. Simulational Algorithms

   • N. Balakrishnan, Rita Aggarwala

   Pages 31-40

5. Recursive Computation and Algorithms

   • N. Balakrishnan, Rita Aggarwala

   Pages 41-65

6. Alternative Computational Methods

   • N. Balakrishnan, Rita Aggarwala

   Pages 67-83

7. Linear Inference

   • N. Balakrishnan, Rita Aggarwala

   Pages 85-115

8. Likelihood Inference: Type-I and Type-II Censoring

   • N. Balakrishnan, Rita Aggarwala

   Pages 117-138

9. Linear Prediction

   • N. Balakrishnan, Rita Aggarwala

   Pages 139-165

10. Conditional Inference

    • N. Balakrishnan, Rita Aggarwala

    Pages 167-181

11. Optimal Censoring Schemes

    • N. Balakrishnan, Rita Aggarwala

    Pages 183-214

12. Acceptance Sampling Plans

    • N. Balakrishnan, Rita Aggarwala

    Pages 215-222

13. Back Matter

    Pages 223-248

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 At the time of the first failure, Rl of the n - 1 surviving units are randomly withdrawn (or censored) from the life-testing experiment.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

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

• Department of Mathematics and Statistics, McMaster University, Hamilton, Canada

  N. Balakrishnan

• Department of Mathematics and Statistics, University of Calgary, Calgary, Canada

  Rita Aggarwala