Statistical Inference On Residual Life
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Statistical Inference On Residual Life
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Author : Jong-Hyeon Jeong
language : en
Publisher: Springer Science & Business Media
Release Date : 2014-01-20
Statistical Inference On Residual Life written by Jong-Hyeon Jeong and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-20 with Medical categories.
This is a monograph on the concept of residual life, which is an alternative summary measure of time-to-event data, or survival data. The mean residual life has been used for many years under the name of life expectancy, so it is a natural concept for summarizing survival or reliability data. It is also more interpretable than the popular hazard function, especially for communications between patients and physicians regarding the efficacy of a new drug in the medical field. This book reviews existing statistical methods to infer the residual life distribution. The review and comparison includes existing inference methods for mean and median, or quantile, residual life analysis through medical data examples. The concept of the residual life is also extended to competing risks analysis. The targeted audience includes biostatisticians, graduate students, and PhD (bio)statisticians. Knowledge in survival analysis at an introductory graduate level is advisable prior to reading this book.
Statistical Inference Based On Kernel Distribution Function Estimators
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Author : Rizky Reza Fauzi
language : en
Publisher: Springer Nature
Release Date : 2023-05-31
Statistical Inference Based On Kernel Distribution Function Estimators written by Rizky Reza Fauzi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-31 with Mathematics categories.
This book presents a study of statistical inferences based on the kernel-type estimators of distribution functions. The inferences involve matters such as quantile estimation, nonparametric tests, and mean residual life expectation, to name just some. Convergence rates for the kernel estimators of density functions are slower than ordinary parametric estimators, which have root-n consistency. If the appropriate kernel function is used, the kernel estimators of the distribution functions recover the root-n consistency, and the inferences based on kernel distribution estimators have root-n consistency. Further, the kernel-type estimator produces smooth estimation results. The estimators based on the empirical distribution function have discrete distribution, and the normal approximation cannot be improved—that is, the validity of the Edgeworth expansion cannot be proved. If the support of the population density function is bounded, there is a boundary problem, namely the estimator does not have consistency near the boundary. The book also contains a study of the mean squared errors of the estimators and the Edgeworth expansion for quantile estimators.
Residual Life Prediction And Optimal Maintenance Decision For A Piece Of Equipment
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Author : Changhua Hu
language : en
Publisher: Springer Nature
Release Date : 2021-07-30
Residual Life Prediction And Optimal Maintenance Decision For A Piece Of Equipment written by Changhua Hu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-30 with Technology & Engineering categories.
This book addresses remaining life prediction and predictive maintenance of equipment. It systematically summarizes the key research findings made by the author and his team and focuses on how to create equipment performance degradation and residual life prediction models based on the performance monitoring data produced by currently used and historical equipment. Some of the theoretical results covered here have been used to make remaining life predictions and maintenance-related decisions for aerospace products such as gyros and platforms. Given its scope, the book offers a valuable reference guide for those pursuing theoretical or applied research in the areas of fault diagnosis and fault-tolerant control, remaining life prediction, and maintenance decision-making.
Statistical Modeling For Biological Systems
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Author : Anthony Almudevar
language : en
Publisher: Springer Nature
Release Date : 2020-03-11
Statistical Modeling For Biological Systems written by Anthony Almudevar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-11 with Medical categories.
This book commemorates the scientific contributions of distinguished statistician, Andrei Yakovlev. It reflects upon Dr. Yakovlev’s many research interests including stochastic modeling and the analysis of micro-array data, and throughout the book it emphasizes applications of the theory in biology, medicine and public health. The contributions to this volume are divided into two parts. Part A consists of original research articles, which can be roughly grouped into four thematic areas: (i) branching processes, especially as models for cell kinetics, (ii) multiple testing issues as they arise in the analysis of biologic data, (iii) applications of mathematical models and of new inferential techniques in epidemiology, and (iv) contributions to statistical methodology, with an emphasis on the modeling and analysis of survival time data. Part B consists of methodological research reported as a short communication, ending with some personal reflections on research fields associated with Andrei and on his approach to science. The Appendix contains an abbreviated vitae and a list of Andrei’s publications, complete as far as we know. The contributions in this book are written by Dr. Yakovlev’s collaborators and notable statisticians including former presidents of the Institute of Mathematical Statistics and of the Statistics Section of the AAAS. Dr. Yakovlev’s research appeared in four books and almost 200 scientific papers, in mathematics, statistics, biomathematics and biology journals. Ultimately this book offers a tribute to Dr. Yakovlev’s work and recognizes the legacy of his contributions in the biostatistics community.
Model Based Inference In The Life Sciences
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Author : David R. Anderson
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-22
Model Based Inference In The Life Sciences written by David R. Anderson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-22 with Science categories.
This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.
Probability Models In Reliability Analysis
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Author : S. P. Mukherjee
language : en
Publisher: Springer Nature
Release Date : 2025-07-01
Probability Models In Reliability Analysis written by S. P. Mukherjee and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Mathematics categories.
This book delves into the fundamental theoretical aspects of reliability analysis, focusing on various probabilistic models. These models are essential for representing random variations in underlying variables such as time-to-failure, the number of failures between consecutive repairs and similar metrics. The calculation, estimation and prediction of reliability all hinge on using appropriate probability models. The book introduces various models beneficial for researchers in the field of reliability. It also provides a comprehensive overview of the available models, highlighting their distinctive features and practical applications in a narrative format. The content of the book is designed to appeal to a broad readership. Students and researchers in the field of reliability analysis will find a comprehensive yet easily understandable summary of models applicable to their data sets of interest. It should be noted, however, As stated clearly in the preface, this book does not illustrate applications of the models discussed in terms of real-life data.
Stochastic Ageing And Dependence For Reliability
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Author : Chin Diew Lai
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-09-24
Stochastic Ageing And Dependence For Reliability written by Chin Diew Lai and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-24 with Mathematics categories.
Ageing and dependence are two important characteristics in reliability and survival analysis, and they affect significantly the decision people make with regard to maintenance, repair/replacement, price setting, warranties, medical studies, and other areas. There are many papers published at different technical levels. This book aims at providing a state-of-the-art review of the subject so the interested readers may have a panoramic view of the theory and applications of the two areas. This book serves as reference book for professors and researchers involved in reliability and survival analysis. Students with basic probability and statistics knowledge interested in applications will also find the book useful. From the reviews: "This book is an important addition to several well-written books on reliability theory and concepts. The book fulfills the authors aim in providing a comprehensive treatment of both ageing and dependence concepts, with emphasis on reliability and survival analysis....Overall, I recommend this book to all serious-minded researchers, practitioners, teachers, and graduate students who would like to have the most up-to-date information available on the subject of stochastic ageing and dependencies in reliability. It also serves as reference book on reliability and survival analysis and is a good addition to one's statistical or reliability library." Suprasad V. Amari, International Journal of Performability Engineering, Vol. 3, No. 2, April 2007
Lifetime Analysis By Aging Intensity Functions
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Author : Magdalena Szymkowiak
language : en
Publisher: Springer
Release Date : 2019-02-01
Lifetime Analysis By Aging Intensity Functions written by Magdalena Szymkowiak and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-01 with Technology & Engineering categories.
This book addresses a range of aging intensity functions, which make it possible to measure and compare aging trends for lifetime random variables. Moreover, they can be used for the characterization of lifetime distributions, also with bounded support. Stochastic orders based on the aging intensities, and their connections with some other orders, are also discussed. To demonstrate the applicability of aging intensity in reliability practice, the book analyzes both real and generated data. The estimated, properly chosen, aging intensity function is mainly recommended to identify data’s lifetime distribution, and secondly, to estimate some of the parameters of the identified distribution. Both reliability researchers and practitioners will find the book a valuable guide and source of inspiration.
Failure Rate Modelling For Reliability And Risk
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Author : Maxim Finkelstein
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-11-07
Failure Rate Modelling For Reliability And Risk written by Maxim Finkelstein and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-07 with Technology & Engineering categories.
“Failure Rate Modeling for Reliability and Risk” focuses on reliability theory, and to the failure rate (hazard rate, force of mortality) modeling and its generalizations to systems operating in a random environment and to repairable systems. The failure rate is one of the crucial probabilistic characteristics for a number of disciplines; including reliability, survival analysis, risk analysis and demography. The book presents a systematic study of the failure rate and related indices, and covers a number of important applications where the failure rate plays the major role. Applications in engineering systems are studied, together with some actuarial, biological and demographic examples. The book provides a survey of this broad and interdisciplinary subject which will be invaluable to researchers and advanced students in reliability engineering and applied statistics, as well as to demographers, econometricians, actuaries and many other mathematically oriented researchers.
Statistical Reliability Engineering
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Author : Hoang Pham
language : en
Publisher: Springer Nature
Release Date : 2021-08-13
Statistical Reliability Engineering written by Hoang Pham and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-13 with Technology & Engineering categories.
This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the author’s recent research and publications as well as experience of over 30 years in this field. The book covers a wide range of methods and models in reliability, and their applications, including: statistical methods and model selection for machine learning; models for maintenance and software reliability; statistical reliability estimation of complex systems; and statistical reliability analysis of k out of n systems, standby systems and repairable systems. Offering numerous examples and solved problems within each chapter, this comprehensive text provides an introduction to reliability engineering graduate students, a reference for data scientists and reliability engineers, and a thorough guide for researchers and instructors in the field.