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.
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. 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
1. Introduction 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