Hybrid Censoring Know-How: Models, Methods and Applications focuses on hybrid censoring, an important topic in censoring methodology with numerous applications. The 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.

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

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Yes, you can access Hybrid Censoring Know-How by Narayanaswamy Balakrishnan,Erhard Cramer,Debasis Kundu in PDF and/or ePUB format, as well as other popular books in Mathématiques & Mathématiques générales. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Academic Press

Year

2023

ISBN

9780123983909

Topic

Mathématiques

Subtopic

Mathématiques générales

Cover image
Title page
Table of Contents
Copyright
Dedication
Preface
Chapter 1: Introduction
Chapter 2: Preliminaries
Chapter 3: Inference for Type-II, Type-I, and progressive censoring
Chapter 4: Models and distributional properties of hybrid censoring designs
Chapter 5: Inference for exponentially distributed lifetimes
Chapter 6: Inference for other lifetime distributions
Chapter 7: Progressive hybrid censored data
Chapter 8: Information measures
Chapter 9: Step-stress testing
Chapter 10: Applications in reliability
Chapter 11: Goodness-of-fit tests
Chapter 12: Prediction methods
Chapter 13: Adaptive progressive hybrid censoring
Appendix
Bibliography
Index