Skip to main content
SpringerLink
Log in
SpringerLink
Log in
Birkhäuser

Progressive Censoring

Theory, Methods, and Applications

  • Book
  • © 2000

Overview

Authors:
  1. N. Balakrishnan

    1. Department of Mathematics and Statistics, McMaster University, Hamilton, Canada

    View author publications

    You can also search for this author in PubMed   Google Scholar

  2. Rita Aggarwala

    1. Department of Mathematics and Statistics, University of Calgary, Calgary, Canada

    View author publications

    You can also search for this author in PubMed   Google Scholar

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

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 199.00
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (11 chapters)

  1. Front Matter

    Pages i-xv
    Download chapter PDF

  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
    Download chapter PDF
Back to top

Keywords

About this book

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).

Authors and Affiliations

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

    N. Balakrishnan

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

    Rita Aggarwala

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation