Hybrid Censoring Know-How
Designs and Implementations
- 1st Edition - January 6, 2023
- Imprint: Academic Press
- Authors: Narayanaswamy Balakrishnan, Erhard Cramer, Debasis Kundu
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 3 9 8 3 8 7 - 9
- eBook ISBN:9 7 8 - 0 - 1 2 - 3 9 8 3 9 0 - 9
Hybrid Censoring Know-How: Models, Methods and Applications focuses on hybrid censoring, an important topic in censoring methodology with numerous applications. The readers w… Read more
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Request a sales quoteHybrid 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
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
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- Preface
- Chapter 1: Introduction
- Abstract
- 1.1. Historical perspectives
- 1.2. Type-I and Type-II censoring
- 1.3. Need for hybrid censoring
- 1.4. Antecedents
- 1.5. Burgeoning literature
- 1.6. Scope of the book
- 1.7. Notation
- Bibliography
- Chapter 2: Preliminaries
- Abstract
- 2.1. Introduction
- 2.2. Order statistics
- 2.3. Progressively Type-II right censored order statistics
- 2.4. Generalized order statistics
- 2.5. Sequential order statistics
- Bibliography
- Chapter 3: Inference for Type-II, Type-I, and progressive censoring
- Abstract
- 3.1. Introduction
- 3.2. Type-II censoring
- 3.3. Type-I censoring
- 3.4. Progressive Type-II censoring
- 3.5. Progressive Type-I censoring
- Bibliography
- Chapter 4: Models and distributional properties of hybrid censoring designs
- Abstract
- 4.1. Introduction
- 4.2. Preliminaries
- 4.3. Type-I hybrid censoring
- 4.4. Type-II hybrid censoring
- 4.5. Further hybrid censoring schemes
- 4.6. Joint (hybrid) censoring
- Bibliography
- Chapter 5: Inference for exponentially distributed lifetimes
- Abstract
- 5.1. Introduction
- 5.2. General expression for the likelihood function
- 5.3. Type-I hybrid censoring
- 5.4. Type-II hybrid censoring
- 5.5. Further hybrid censoring schemes
- Bibliography
- Chapter 6: Inference for other lifetime distributions
- Abstract
- 6.1. Introduction
- 6.2. Weibull distributions
- 6.3. Further distributions
- Bibliography
- Chapter 7: Progressive hybrid censored data
- Abstract
- 7.1. Progressive (hybrid) censoring schemes
- 7.2. Exponential case: MLEs and its distribution
- 7.3. Progressive hybrid censored data: other cases
- Bibliography
- Chapter 8: Information measures
- Abstract
- 8.1. Introduction
- 8.2. Fisher information
- 8.3. Entropy
- 8.4. Kullback-Leibler information
- 8.5. Pitman closeness
- Bibliography
- Chapter 9: Step-stress testing
- Abstract
- 9.1. Introduction
- 9.2. Step-stress models under censoring
- 9.3. Step stress models under hybrid censoring
- Bibliography
- Chapter 10: Applications in reliability
- Abstract
- 10.1. Introduction
- 10.2. Competing risks analysis
- 10.3. Stress-strength models
- 10.4. Optimal designs
- 10.5. Reliability acceptance sampling plans
- Bibliography
- Chapter 11: Goodness-of-fit tests
- Abstract
- 11.1. Introduction
- 11.2. Progressive censoring
- 11.3. Hybrid censoring
- Bibliography
- Chapter 12: Prediction methods
- Abstract
- 12.1. Introduction
- 12.2. Point prediction
- 12.3. Interval prediction
- Bibliography
- Chapter 13: Adaptive progressive hybrid censoring
- Abstract
- 13.1. Introduction
- 13.2. Adaptive Type-II progressive hybrid censoring
- 13.3. Inference for adaptive Type-II progressive hybrid censored data
- 13.4. Adaptive Type-I progressive hybrid censoring
- Bibliography
- Appendix
- A. Geometrical objects
- B. Distributions
- C. B-splines and divided differences
- Bibliography
- Bibliography
- Bibliography
- Index
- Edition: 1
- Published: January 6, 2023
- No. of pages (Hardback): 406
- No. of pages (eBook): 406
- Imprint: Academic Press
- Language: English
- Hardback ISBN: 9780123983879
- eBook ISBN: 9780123983909
NB
Narayanaswamy Balakrishnan
Narayanaswamy Balakrishnan is a distinguished university professor in the Department of Mathematics and Statistics at McMaster University Hamilton, Ontario, Canada. He is an internationally recognized expert on statistical distribution theory, and a book-powerhouse with over 24 authored books, four authored handbooks, and 30 edited books under his name. He is currently the Editor-in-Chief of Communications in Statistics published by Taylor & Francis. He 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. In 2016, he 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
Distinguished University Professor, Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, CanadaEC
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 coauthor of the book The Art of Progressive Censoring: Applications to Reliability and Quality published by Birkhäuser, Boston, in 2014.
Affiliations and expertise
Institute for Statistics and Business Mathematics, RWTH Aachen, Aachen, GermanyDK
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, nonlinear 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, IndiaRead Hybrid Censoring Know-How on ScienceDirect