Hybrid Censoring: Models, Methods and Applications

1st Edition

for Engineering and Bio Health


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Hybrid Censoring: Models, Methods and Applications for Engineering and Bio Health focuses on hybrid censoring, a specific yet important topic in censoring methodology that has numerous applications. Readers will find information on the significance of censored data in theoretical and applied contexts and descriptions of extensive data sets from life-testing experiments where these forms of data naturally occur.

The existing literature on censoring methodology, life-testing procedures, or lifetime data analysis provides only hybrid censoring schemes, with little information about hybrid censoring methodologies, ideas, and statistical inferential methods. This book fills that gap by providing readers with valuable information on these topics. The statistical tools presented are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography.

Key Features

  • Presents many numerical examples to adequately illustrate all the inferential methods discussed
  • Provides open problems and possible directions for future work
  • Reviews developments pertaining to Type-II HCS, and includes the most recent research and trends
  • Explains why the hybrid censored sampling is important
  • Provides detail in using HCS under different settings and the designs of HCS
  • Includes R code on website for ease of use


Life science and engineering scientists and researchers who need to analyze censored or truncated life time data and students, researchers and practitioners in different areas such as statistics, industrial engineering and clinical trials

Table of Contents

Chapter 1. Introduction
Chapter 2. Basic Forms of Censoring
Chapter 3. Models of Hybrid Censoring
Chapter 4. Type-I HCS
Chapter 5. Type-II HCS
Chapter 6. Generalized HCS
Chapter 7. HCS in Presence of Competing Risks
Chapter 8. Type-I Progressive HCS
Chapter 9. Type-II Progressive HCS
Chapter 10. Adaptive Progressive HCS
Chapter 11. Step-Stress Tests with HCS
Chapter 12. Reliability Sampling Plans with HCS
Chapter 13. Some Other Developments on HCS, Bibliography


No. of pages:
© 2017
Academic Press
eBook ISBN:
Print ISBN:

About the authors

N. Balakrishnan

Professor Narayanaswamy Balakrishnan, Professor of Statistics, Department of Mathematics and Statistics McMaster University Hamilton, Ontario, Canada & visiting Professor, King Abdulaziz University, Jeddah, Saudi Arabia. Balakrishnan is a statistical distribution theorist and books powerhouse with 16 authored books, 4 authored handbooks, and 27 edited books under his name. He is current Editor-in-Chief of Communications in Statistics, and for the revised Encyclopedia of Statistical Sciences published by Wiley.

Affiliations and Expertise

McMaster University, Hamilton, Canada

Debasis Kundu

His research interests are Statistical Signal Processing, Distribution Theory and Reliability & Survival Analysis. Recipient of the Distinguished Statistician Award by the Indian Society of Probability and Statistics, 2014

Affiliations and Expertise

Rahul and Namita Gautam Chair Professor, Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, India