Hybrid Censoring Know-How

Hybrid Censoring Know-How

Models, Methods and Applications

1st Edition - February 1, 2023

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  • Authors: Narayanaswamy Balakrishnan, Erhard Cramer, Debasis Kundu
  • Hardcover ISBN: 9780123983879

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Hybrid Censoring Know-How: Models, Methods and Applications focuses on hybrid censoring, an important topic in censoring methodology with 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, and 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, featuring statistical tools applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography.

Key Features

  • Presents many numerical examples to adequately illustrate all inferential methods discussed
  • Mentions some open problems and possible directions for future work
  • Reviews developments on Type-II and Type-I HCS, including the most recent research and trends
  • Explains why hybrid censored sampling is important in practice
  • Provides details about the use of HCS under different settings and on various designs of HCS
  • Describes the use of hybrid censoring in other reliability applications such as reliability sampling plans, step-stress testing and quality control


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

  • 1. Introduction
    2. Preliminaries
    3. Models and Distributional Properties
    4. Inference for Exponentially Distributed Lifetimes
    5. Inference for Other Lifetime Distributions
    6. Progressive Hybrid Censored Data
    7. Information Measures
    8. Optimal Designs
    9. Applications in Reliability
    10. Statistical tests
    11. Prediction Methods
    12. Conclusions

Product details

  • No. of pages: 330
  • Language: English
  • Copyright: © Academic Press 2023
  • Published: February 1, 2023
  • Imprint: Academic Press
  • Hardcover ISBN: 9780123983879

About the Authors

Narayanaswamy Balakrishnan

Narayanaswamy Balakrishnan
Narayanaswamy Balakrishnan, Distinguished University Professor, is in the Department of Mathematics and Statistics McMaster University Hamilton, Ontario, Canada. Professor Balakrishnan is an internationally recognized expert on statistical distribution theory, and a book-powerhouse with 24 authored books, 4 authored handbooks, and 30 edited books under his name. He is currently the Editor-in-Chief of Communications in Statistics published by Taylor & Francis, and was also the Editor-in-Chief for the revised version of Encyclopedia of Statistical Sciences published by John Wiley & Sons. He is a Fellow of the American Statistical Association and a Fellow of the Institute of Mathematical Statistics, and in 2016 was awarded an Honorary Doctorate from The National and Kapodistrian University of Athens, Athens, Greece. In 2021, he was elected as a Fellow of the Royal Society of Canada.

Affiliations and Expertise

Professor of Statistics, Department of Mathematics and Statistics McMaster University Hamilton, Ontario, Canada; visiting Professor, King Abdulaziz University, Jeddah, Saudi Arabi

Erhard Cramer

Erhard Cramer is a Professor in the Institute for Statistics at RWTH Aachen University in Aachen, Germany. He has numerous publications to his credit and his research interests include order statistics, generalized order statistics, censoring methodology, B-spline theory, and statistical inference. He is a co-author of the book The Art of Progressive Censoring: Applications to Reliability and Quality published by Birkhauser, Boston, in 2014.

Affiliations and Expertise

Institute for Statistics and Business Mathematics, RWTH Aachen, Aachen, Germany

Debasis Kundu

Debasis Kundu is a Professor in the Department of Mathematics and Statistics, at the Indian Institute of Technology Kanpur, India, which he joined in 1990. He had previously worked as Assistant Professor at the University of Texas at Dallas, USA, after completing his PhD in Statistics at Pennsylvania State University, USA. His research interests include statistical signal processing, non-linear regression, distribution theory, statistical computing, and reliability and survival analysis.

Affiliations and Expertise

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

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