This new book offers a guide to the theory and methods of progressive censoring. In many industrial experiments involving lifetimes of machines or units, experiments have to be terminated early. Progressive Censoring first introduces progressive sampling foundations, and then discusses various properties of progressive samples. The book points out the greater efficiency gained by using this scheme instead of classical right-censoring methods.
This book offers a thorough and updated guide to the theory and methods of progressive censoring, an area that has experienced tremendous growth over the last decade. The theory has developed quite nicely in some special cases having practical applications to reliability and quality. The Art of Progressive Censoring is a valuable reference for graduate students, researchers, and practitioners in applied statistics, quality control, life testing, and reliability. With its accessible style and concrete examples, the work may also be used as a textbook in an advanced undergraduate or a beginning graduate course on censoring or progressive censoring, as well as a supplementary textbook for a course on ordered data.
This book deals with the mathematical aspects of survival analysis and reliability as well as other topics, reflecting recent developments in the following areas: applications in epidemiology; probabilistic and statistical models and methods in reliability; models and methods in survival analysis, longevity, aging, and degradation; accelerated life models; quality of life; new statistical challenges in genomics. The work will be useful to a broad interdisciplinary readership of researchers and practitioners in applied probability and statistics, industrial statistics, biomedicine, biostatistics, and engineering.
In The Case Against the New Censorship: Protecting Free Speech from Big Tech, Progressives, and Universities, Alan Dershowitz—New York Times bestselling author and one of America’s most respected legal scholars—analyzes the current regressive war against freedom of speech being waged by well-meaning but dangerous censors and proposes steps that can be taken to defend, reclaim, and strengthen freedom of speech and other basic liberties that are under attack. Alan Dershowitz has been called “one of the most prominent and consistent defenders of civil liberties in America” by Politico and “the nation’s most peripatetic civil liberties lawyer and one of its most distinguished defenders of individual rights” by Newsweek. He is also a fair-minded and even-handed expert on the Constitution and our civil liberties, and in this book offers his knowledge and insight to help readers understand the war being waged against free speech by the ostensibly well-meaning forces seeking to constrain this basic right. The Case Against the New Censorship is an analysis of every aspect of the current fight against freedom of speech, from the cancellations and deplatformings practiced by so-called progressives, to the powerful, seemingly arbitrary control exerted by Big Tech and social media companies, to the stifling of debate and controversial thinking at public and private universities. It assesses the role of the Trump presidency in energizing this backlash against basic liberties and puts it into a broader historical context as it examines how anti-Trump zealots weaponized, distorted, and weakened constitutional protections in an effort to “get” Trump by any means. In the end, The Case Against the New Censorship represents an icon in American law and politics exploring the current rapidly changing attitudes toward the value of free speech and assessing potential ways to preserve our civil liberties. It is essential reading for anyone interested in or concerned about freedom of speech and the efforts to constrain it, the possible effects this could have on our society, and the significance of both freedom of speech and the battle against it in a greater historical and political context.
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
S. Panchapakesan has made significant contributions to ranking and selection and has published in many other areas of statistics, including order statistics, reliability theory, stochastic inequalities, and inference. Written in his honor, the twenty invited articles in this volume reflect recent advances in these areas and form a tribute to Panchapakesan’s influence and impact on these areas. Featuring theory, methods, applications, and extensive bibliographies with special emphasis on recent literature, this comprehensive reference work will serve researchers, practitioners, and graduate students in the statistical and applied mathematics communities.
This volume presents an eclectic mix of original research articles in areas covering the analysis of ordered data, stochastic modeling and biostatistics. These areas were featured in a conference held at the University of Texas at Dallas from March 7 to 9, 2014 in honor of Professor H. N. Nagaraja’s 60th birthday and his distinguished contributions to statistics. The articles were written by leading experts who were invited to contribute to the volume from among the conference participants. The volume is intended for all researchers with an interest in order statistics, distribution theory, analysis of censored data, stochastic modeling, time series analysis, and statistical methods for the health sciences, including statistical genetics.
In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness.
Making complex methods more accessible to applied researchers without an advanced mathematical background, the authors present the essence of new techniques available, as well as classical techniques, and apply them to data. Practical suggestions for implementing the various methods are set off in a series of practical notes at the end of each section, while technical details of the derivation of the techniques are sketched in the technical notes. This book will thus be useful for investigators who need to analyse censored or truncated life time data, and as a textbook for a graduate course in survival analysis, the only prerequisite being a standard course in statistical methodology.
Bayesian analysis is one of the important tools for statistical modelling and inference. Bayesian frameworks and methods have been successfully applied to solve practical problems in reliability and survival analysis, which have a wide range of real world applications in medical and biological sciences, social and economic sciences, and engineering. In the past few decades, significant developments of Bayesian inference have been made by many researchers, and advancements in computational technology and computer performance has laid the groundwork for new opportunities in Bayesian computation for practitioners. Because these theoretical and technological developments introduce new questions and challenges, and increase the complexity of the Bayesian framework, this book brings together experts engaged in groundbreaking research on Bayesian inference and computation to discuss important issues, with emphasis on applications to reliability and survival analysis. Topics covered are timely and have the potential to influence the interacting worlds of biostatistics, engineering, medical sciences, statistics, and more. The included chapters present current methods, theories, and applications in the diverse area of biostatistical analysis. The volume as a whole serves as reference in driving quality global health research.
