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.
- 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
2. Basic Forms of Censoring
3. Models of Hybrid Censoring
4. Type-I HCS
5. Type-II HCS
6. Generalized HCS
7. HCS in Presence of Competing Risks
8. Type-I Progressive HCS
9. Type-II Progressive HCS
10. Adaptive Progressive HCS
11. Step-Stress Tests with HCS
12. Reliability Sampling Plans with HCS
13. Some Other Developments on HCS, Bibliography
- No. of pages:
- © Academic Press 2029
- 1st October 2029
- Academic Press
- eBook ISBN:
- Hardcover ISBN:
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.
McMaster University, Hamilton, Canada
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.
Rahul and Namita Gautam Chair Professor, Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, India