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The Birnbaum-Saunders Distribution

The Birnbaum-Saunders Distribution
  • Author : Victor Leiva
  • Publisher :Unknown
  • Release Date :2015-10-26
  • Total pages :154
  • ISBN : 9780128038277
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Summary : The Birnbaum-Saunders Distribution presents the statistical theory, methodology, and applications of the Birnbaum-Saunders distribution, a very flexible distribution for modeling different types of data (mainly lifetime data). The book describes the most recent theoretical developments of this model, including properties, transformations and related distributions, lifetime analysis, and shape analysis. It discusses methods of inference based on uncensored and censored data, goodness-of-fit tests, and random number generation algorithms for the Birnbaum-Saunders distribution, also presenting existing and future applications. Introduces inference in the Birnbaum-Saunders distribution Provides a comprehensive review of the statistical theory and methodology of the Birnbaum-Distribution Discusses different applications of the Birnbaum-Saunders distribution Explains characterization and the lifetime analysis

The Birnbaum-Saunders Distribution

The Birnbaum-Saunders Distribution
  • Author : Victor Leiva
  • Publisher :Unknown
  • Release Date :2015-10-01
  • Total pages :154
  • ISBN : 0128037695
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Summary : The Birnbaum-Saunders Distribution presents the statistical theory, methodology, and applications of the Birnbaum-Saunders distribution, a very flexible distribution for modeling different types of data (mainly lifetime data). The book describes the most recent theoretical developments of this model, including properties, transformations and related distributions, lifetime analysis, and shape analysis. It discusses methods of inference based on uncensored and censored data, goodness-of-fit tests, and random number generation algorithms for the Birnbaum-Saunders distribution, also presenting existing and future applications. Introduces inference in the Birnbaum-Saunders distribution Provides a comprehensive review of the statistical theory and methodology of the Birnbaum-Distribution Discusses different applications of the Birnbaum-Saunders distribution Explains characterization and the lifetime analysis

Shortest Prediction Intervals for the Birnbaum-Saunders Distribution

Shortest Prediction Intervals for the Birnbaum-Saunders Distribution
  • Author : Zhenlin Yang
  • Publisher :Unknown
  • Release Date :1994
  • Total pages :19
  • ISBN : UCSD:31822018905315
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Summary :

Statistical Analysis for the Birnbaum-Saunders Fatigue Life Distribution

Statistical Analysis for the Birnbaum-Saunders Fatigue Life Distribution
  • Author : James R. Rieck
  • Publisher :Unknown
  • Release Date :1989
  • Total pages :254
  • ISBN : OCLC:19611217
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Summary :

Testing and Inspection Using Acceptance Sampling Plans

Testing and Inspection Using Acceptance Sampling Plans
  • Author : Muhammad Aslam,Mir Masoom Ali
  • Publisher :Unknown
  • Release Date :2019-07-19
  • Total pages :288
  • ISBN : 9789811393068
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Summary : This book introduces a number of new sampling plans, such as time truncated life tests, skip sampling plans, resubmitted plans, mixed sampling plans, sampling plans based on the process capability index and plans for big data, which can be used for testing and inspecting products, from the raw-materials stage to the final product, in every industry using statistical process control techniques. It also presents the statistical theory, methodology and applications of acceptance sampling from truncated life tests. Further, it discusses the latest reliability, quality and risk analysis methods based on acceptance sampling from truncated life, which engineering and statisticians require in order to make decisions, and which are also useful for researchers in the areas of quality control, lifetime analysis, censored data analysis, goodness-of-fit and statistical software applications. In its nine chapters, the book addresses a wide range of testing/inspection sampling schemes for discrete and continuous data collected in various production processes. It includes a chapter on sampling plans for big data and offers several illustrative examples of the procedures presented. Requiring a basic knowledge of probability distributions, inference and estimation, and lifetime and quality analysis, it is a valuable resource for graduate and senior undergraduate engineering students, and practicing engineers, more specifically it is useful for quality engineers, reliability engineers, consultants, black belts, master black belts, students and researchers interested in applying reliability and risk and quality methods.

The Inverse Gaussian Distribution

The Inverse Gaussian Distribution
  • Author : V. Seshadri
  • Publisher :Unknown
  • Release Date :2012-12-06
  • Total pages :347
  • ISBN : 9781461214564
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Summary : This book is written in the hope that it will serve as a companion volume to my first monograph. The first monograph was largely devoted to the probabilistic aspects of the inverse Gaussian law and therefore ignored the statistical issues and related data analyses. Ever since the appearance of the book by Chhikara and Folks, a considerable number of publications in both theory and applications of the inverse Gaussian law have emerged thereby justifying the need for a comprehensive treatment of the issues involved. This book is divided into two sections and fills up the gap updating the material found in the book of Chhikara and Folks. Part I contains seven chapters and covers distribution theory, estimation, significance tests, goodness-of-fit, sequential analysis and compound laws and mixtures. The first part forms the backbone of the theory and wherever possible I have provided illustrative examples for easy assimilation of the theory. The second part is devoted to a wide range of applications from various disciplines. The applied statistician will find numerous instances of examples which pertain to a first passage time situation. It is indeed remarkable that in the fields of life testing, ecology, entomology, health sciences, traffic intensity and management science the inverse Gaussian law plays a dominant role. Real life examples from actuarial science and ecology came to my attention after this project was completed and I found it impossible to include them.

First Hitting Time Regression Models

First Hitting Time Regression Models
  • Author : Chrysseis Caroni
  • Publisher :Unknown
  • Release Date :2017-07-17
  • Total pages :200
  • ISBN : 9781119437222
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Summary : This book aims to promote regression methods for analyzing lifetime (or time-to-event) data that are based on a representation of the underlying process, and are therefore likely to offer greater scientific insight compared to purely empirical methods. In contrast to the rich statistical literature, the regression methods actually employed in lifetime data analysis are limited, particularly in the biomedical field where D. R. Cox’s famous semi-parametric proportional hazards model predominates. Practitioners should become familiar with more flexible models. The first hitting time regression models (or threshold regression) presented here represent observed events as the outcome of an underlying stochastic process. One example is death occurring when the patient’s health status falls to zero, but the idea has wide applicability – in biology, engineering, banking and finance, and elsewhere. The central topic is the model based on an underlying Wiener process, leading to lifetimes following the inverse Gaussian distribution. Introducing time-varying covariates and many other extensions are considered. Various applications are presented in detail.

Elliptically Contoured Models in Statistics

Elliptically Contoured Models in Statistics
  • Author : Arjun K. Gupta,Tamas Varga
  • Publisher :Unknown
  • Release Date :2012-12-06
  • Total pages :327
  • ISBN : 9789401116466
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Summary : In multivariate statistical analysis, elliptical distributions have recently provided an alternative to the normal model. Most of the work, however, is spread out in journals throughout the world and is not easily accessible to the investigators. Fang, Kotz, and Ng presented a systematic study of multivariate elliptical distributions, however, they did not discuss the matrix variate case. Recently Fang and Zhang have summarized the results of generalized multivariate analysis which include vector as well as the matrix variate distributions. On the other hand, Fang and Anderson collected research papers on matrix variate elliptical distributions, many of them published for the first time in English. They published very rich material on the topic, but the results are given in paper form which does not provide a unified treatment of the theory. Therefore, it seemed appropriate to collect the most important results on the theory of matrix variate elliptically contoured distributions available in the literature and organize them in a unified manner that can serve as an introduction to the subject. The book will be useful for researchers, teachers, and graduate students in statistics and related fields whose interests involve multivariate statistical analysis. Parts of this book were presented by Arjun K Gupta as a one semester course at Bowling Green State University. Some new results have also been included which generalize the results in Fang and Zhang. Knowledge of matrix algebra and statistics at the level of Anderson is assumed. However, Chapter 1 summarizes some results of matrix algebra.

Statistical Analysis of Fatigue Data

Statistical Analysis of Fatigue Data
  • Author : Robert Eugene Little,J. C. Ekvall
  • Publisher :Unknown
  • Release Date :1981-01-01
  • Total pages :143
  • ISBN : 1230987654XX
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Summary :

Progressive Censoring

Progressive Censoring
  • Author : N. Balakrishnan,Rita Aggarwala
  • Publisher :Unknown
  • Release Date :2012-12-06
  • Total pages :248
  • ISBN : 9781461213345
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Summary : 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.

Computational and Methodological Statistics and Biostatistics

Computational and Methodological Statistics and Biostatistics
  • Author : Andriëtte Bekker
  • Publisher :Unknown
  • Release Date :2021
  • Total pages :229
  • ISBN : 9783030421960
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Summary :

The Gradient Test

The Gradient Test
  • Author : Artur Lemonte
  • Publisher :Unknown
  • Release Date :2016-02-05
  • Total pages :156
  • ISBN : 9780128036136
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Summary : The Gradient Test: Another Likelihood-Based Test presents the latest on the gradient test, a large-sample test that was introduced in statistics literature by George R. Terrell in 2002. The test has been studied by several authors, is simply computed, and can be an interesting alternative to the classical large-sample tests, namely, the likelihood ratio (LR), Wald (W), and Rao score (S) tests. Due to the large literature about the LR, W and S tests, the gradient test is not frequently used to test hypothesis. The book covers topics on the local power of the gradient test, the Bartlett-corrected gradient statistic, the gradient statistic under model misspecification, and the robust gradient-type bounded-influence test. Covers the background of the gradient statistic and the different models Discusses The Bartlett-corrected gradient statistic Explains the algorithm to compute the gradient-type statistic

Order Statistics & Inference

Order Statistics & Inference
  • Author : N. Balakrishnan,A. Clifford Cohen
  • Publisher :Unknown
  • Release Date :2014-06-28
  • Total pages :392
  • ISBN : 9781483297491
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Summary : The literature on order statistics and inferenc eis quite extensive and covers a large number of fields ,but most of it is dispersed throughout numerous publications. This volume is the consolidtion of the most important results and places an emphasis on estimation. Both theoretical and computational procedures are presented to meet the needs of researchers, professionals, and students. The methods of estimation discussed are well-illustrated with numerous practical examples from both the physical and life sciences, including sociology,psychology,a nd electrical and chemical engineering. A complete, comprehensive bibliography is included so the book can be used both aas a text and reference.

Aspects of Inference in the Birnbaum-saunders and Sinh-normal Distributions

Aspects of Inference in the Birnbaum-saunders and Sinh-normal Distributions
  • Author : Carlos L. Cintora Gonzalez,University of Guelph. Department of Mathematics and Statistics
  • Publisher :Unknown
  • Release Date :2007
  • Total pages :147
  • ISBN : 049433598X
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Summary :

Statistical Methods for Reliability Data

Statistical Methods for Reliability Data
  • Author : William Q. Meeker,Luis A. Escobar
  • Publisher :Unknown
  • Release Date :2014-08-21
  • Total pages :712
  • ISBN : 9781118625972
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Summary : Amstat News asked three review editors to rate their top five favorite books in the September 2003 issue. Statistical Methods for Reliability Data was among those chosen. Bringing statistical methods for reliability testing in line with the computer age This volume presents state-of-the-art, computer-based statistical methods for reliability data analysis and test planning for industrial products. Statistical Methods for Reliability Data updates and improves established techniques as it demonstrates how to apply the new graphical, numerical, or simulation-based methods to a broad range of models encountered in reliability data analysis. It includes methods for planning reliability studies and analyzing degradation data, simulation methods used to complement large-sample asymptotic theory, general likelihood-based methods of handling arbitrarily censored data and truncated data, and more. In this book, engineers and statisticians in industry and academia will find: A wealth of information and procedures developed to give products a competitive edge Simple examples of data analysis computed with the S-PLUS system-for which a suite of functions and commands is available over the Internet End-of-chapter, real-data exercise sets Hundreds of computer graphics illustrating data, results of analyses, and technical concepts An essential resource for practitioners involved in product reliability and design decisions, Statistical Methods for Reliability Data is also an excellent textbook for on-the-job training courses, and for university courses on applied reliability data analysis at the graduate level. An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon requestfrom the Wiley editorial department.

Statistics

Statistics
  • Author : Michael J. Crawley
  • Publisher :Unknown
  • Release Date :2005-05-06
  • Total pages :342
  • ISBN : 0470022981
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Summary : Computer software is an essential tool for many statistical modelling and data analysis techniques, aiding in the implementation of large data sets in order to obtain useful results. R is one of the most powerful and flexible statistical software packages available, and enables the user to apply a wide variety of statistical methods ranging from simple regression to generalized linear modelling. Statistics: An Introduction using R is a clear and concise introductory textbook to statistical analysis using this powerful and free software, and follows on from the success of the author's previous best-selling title Statistical Computing. * Features step-by-step instructions that assume no mathematics, statistics or programming background, helping the non-statistician to fully understand the methodology. * Uses a series of realistic examples, developing step-wise from the simplest cases, with the emphasis on checking the assumptions (e.g. constancy of variance and normality of errors) and the adequacy of the model chosen to fit the data. * The emphasis throughout is on estimation of effect sizes and confidence intervals, rather than on hypothesis testing. * Covers the full range of statistical techniques likely to be need to analyse the data from research projects, including elementary material like t-tests and chi-squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling. * Includes numerous worked examples and exercises within each chapter. * Accompanied by a website featuring worked examples, data sets, exercises and solutions: http://www.imperial.ac.uk/bio/research/crawley/statistics Statistics: An Introduction using R is the first text to offer such a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a broad range of disciplines. It is primarily aimed at undergraduate students in medicine, engineering, economics and biology - but will also appeal to postgraduates who have not previously covered this area, or wish to switch to using R.

Vector Generalized Linear and Additive Models

Vector Generalized Linear and Additive Models
  • Author : Thomas W. Yee
  • Publisher :Unknown
  • Release Date :2015-09-11
  • Total pages :589
  • ISBN : 9781493928187
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Summary : This book presents a greatly enlarged statistical framework compared to generalized linear models (GLMs) with which to approach regression modelling. Comprising of about half-a-dozen major classes of statistical models, and fortified with necessary infrastructure to make the models more fully operable, the framework allows analyses based on many semi-traditional applied statistics models to be performed as a coherent whole. Since their advent in 1972, GLMs have unified important distributions under a single umbrella with enormous implications. However, GLMs are not flexible enough to cope with the demands of practical data analysis. And data-driven GLMs, in the form of generalized additive models (GAMs), are also largely confined to the exponential family. The methodology here and accompanying software (the extensive VGAM R package) are directed at these limitations and are described comprehensively for the first time in one volume. This book treats distributions and classical models as generalized regression models, and the result is a much broader application base for GLMs and GAMs. The book can be used in senior undergraduate or first-year postgraduate courses on GLMs or categorical data analysis and as a methodology resource for VGAM users. In the second part of the book, the R package VGAM allows readers to grasp immediately applications of the methodology. R code is integrated in the text, and datasets are used throughout. Potential applications include ecology, finance, biostatistics, and social sciences. The methodological contribution of this book stands alone and does not require use of the VGAM package.

Probability Distributions Used in Reliability Engineering

Probability Distributions Used in Reliability Engineering
  • Author : Andrew N O'Connor
  • Publisher :Unknown
  • Release Date :2011-01-01
  • Total pages :208
  • ISBN : 9781933904061
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Summary : The book provides details on 22 probability distributions. Each distribution section provides a graphical visualization and formulas for distribution parameters, along with distribution formulas. Common statistics such as moments and percentile formulas are followed by likelihood functions and in many cases the derivation of maximum likelihood estimates. Bayesian non-informative and conjugate priors are provided followed by a discussion on the distribution characteristics and applications in reliability engineering.

Mathematical and Statistical Applications in Life Sciences and Engineering

Mathematical and Statistical Applications in Life Sciences and Engineering
  • Author : Avishek Adhikari,Mahima Ranjan Adhikari,Yogendra Prasad Chaubey
  • Publisher :Unknown
  • Release Date :2017-12-06
  • Total pages :372
  • ISBN : 9789811053702
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Summary : The book includes articles from eminent international scientists discussing a wide spectrum of topics of current importance in mathematics and statistics and their applications. It presents state-of-the-art material along with a clear and detailed review of the relevant topics and issues concerned. The topics discussed include message transmission, colouring problem, control of stochastic structures and information dynamics, image denoising, life testing and reliability, survival and frailty models, analysis of drought periods, prediction of genomic profiles, competing risks, environmental applications and chronic disease control. It is a valuable resource for researchers and practitioners in the relevant areas of mathematics and statistics.

Extreme Values and Financial Risk

Extreme Values and Financial Risk
  • Author : Saralees Nadarajah,Stephen Chan
  • Publisher :Unknown
  • Release Date :2019-01-15
  • Total pages :114
  • ISBN : 9783038974390
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Summary : This book is a printed edition of the Special Issue "Extreme Values and Financial Risk" that was published in JRFM

Generalized Linear Models for Insurance Data

Generalized Linear Models for Insurance Data
  • Author : Piet de Jong,Gillian Z. Heller
  • Publisher :Unknown
  • Release Date :2008-02-28
  • Total pages :229
  • ISBN : 9781139470476
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Summary : This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are provided on the website.