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Author: Chin-Diew Lai
Publisher: Springer Science & Business Media
ISBN: 3642391060
Category : Mathematics
Languages : en
Pages : 121
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Book Description
The Weibull distribution has been one of the most cited lifetime distributions in reliability engineering. Over the last decade, many generalizations and extensions of the Weibull have been proposed in order to provide more flexibility than the traditional version when it comes to modeling lifetime data in diverse fields. This book offers an update on these developments, presenting the essential properties of each model. Several plots of density and hazard rate functions are also included, and a brief outline of known application(s) for each model is also given.
Author: Chin-Diew Lai
Publisher: Springer Science & Business Media
ISBN: 3642391060
Category : Mathematics
Languages : en
Pages : 121
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Book Description
The Weibull distribution has been one of the most cited lifetime distributions in reliability engineering. Over the last decade, many generalizations and extensions of the Weibull have been proposed in order to provide more flexibility than the traditional version when it comes to modeling lifetime data in diverse fields. This book offers an update on these developments, presenting the essential properties of each model. Several plots of density and hazard rate functions are also included, and a brief outline of known application(s) for each model is also given.
Author: Manmohan Singh Arora
Publisher:
ISBN:
Category : Distribution (Probability theory)
Languages : en
Pages : 416
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Book Description
Author: Sarah A. Ayoku
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages :
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Book Description
Author's abstract: In this thesis, a new class of generalized distributions which includes several new distributions is proposed and developed. This new class of distributions called the Burr-XII Weibull (BXIIW) distribution has several other distributions as special cases and includes several well known distributions such as Burr-XII Rayleigh (BXIIR), Burr-XII Exponential (BXIIE), log-logistic-Weibull (LLoGW), and several others. The Burr-XII Weibull (BXIIW) class of distribution is studied in details. Some mathematical properties of this new class of BXIIW distribution including Moments, Conditional Moments, Mean Deviations, Bonferroni and Lorenz curves, distribution of the order statistics and Renyi entropy are presented. Maximum likelihood estimation technique is used to estimate the BXIIW model parameters. A simulation study is conducted to examine the bias, mean square error of the Maximum likelihood estimators and width of the confidence interval for each parameter. Applications to real data sets illustrating the applicability and usefulness of the proposed distribution is presented.
Author: Valeriia Sherina
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages :
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Book Description
Author's abstract: In this thesis, new classes of Weibull and inverse Weibull distributions including the generalized new modified Weibull (GNMW), gamma-generalized inverse Weibull (GGIW), the weighted proportional inverse Weibull (WPIW) and inverse new modified Weibull (INMW) distributions are introduced. The GNMW contains several sub-models including the new modified Weibull (NMW), generalized modified Weibull (GMW), modified Weibull (MW), Weibull (W) and exponential (E) distributions, just to mention a few. The class of WPIW distributions contains several models such as: length-biased, hazard and reverse hazard proportional inverse Weibull, proportional inverse Weibull, inverse Weibull, inverse exponential, inverse Rayleigh, and Frechet distributions as special cases. Included in the GGIW distribution are the sub-models: gamma-generalized inverse Weibull, gamma-generalized Frechet, gamma-generalized inverse Rayleigh, gamma-generalized inverse exponential, inverse Weibull, inverse Rayleigh, inverse exponential, Frechet distributions. The INMW distribution contains several sub-models including inverse Weibull, inverse new modified exponential, inverse new modified Rayleigh, new modified Frechet, inverse modified Weibull, inverse Rayleigh and inverse exponential distributions as special cases. Properties of these distributions including the behavior of the hazard function, moments, coefficients of variation, skewness, and kurtosis, s-entropy, distribution of order statistic and Fisher information are presented. Estimates of the parameters of the models via method of maximum likelihood (ML) are presented. Extensive simulation study is conducted and numerical examples are given.
Author: Unnikrishnan Nair
Publisher: Academic Press
ISBN: 0128020067
Category : Mathematics
Languages : en
Pages : 510
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Book Description
Reliability Modelling and Analysis in Discrete Time provides an overview of the probabilistic and statistical aspects connected with discrete reliability systems. This engaging book discusses their distributional properties and dependence structures before exploring various orderings associated between different reliability structures. Though clear explanations, multiple examples, and exhaustive coverage of the basic and advanced topics of research in this area, the work gives the reader a thorough understanding of the theory and concepts associated with discrete models and reliability structures. A comprehensive bibliography assists readers who are interested in further research and understanding. Requiring only an introductory understanding of statistics, this book offers valuable insight and coverage for students and researchers in Probability and Statistics, Electrical Engineering, and Reliability/Quality Engineering. The book also includes a comprehensive bibliography to assist readers seeking to delve deeper. Includes a valuable introduction to Reliability Theory before covering advanced topics of research and real world applications Features an emphasis on the mathematical theory of reliability modeling Provides many illustrative examples to foster reader understanding
Author: Shusen Pu
Publisher:
ISBN:
Category : Electronic dissertations
Languages : en
Pages :
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Book Description
Author's Abstract: Weibull distribution and its extended families has been widely studied in lifetime applications. Based on the Weibull-G family of distributions and the exponentiated Weibull distribution, we study in detail two new classes of distributions, namely, Gamma-Weibull-G family of distributions (GWG) and gamma-exponentiated or generalized modified Weibull (GEMW) distribution. Some special models in these new classes are discussed. Statistical properties of these family of distributions, such as expansion of density function, hazard and reverse hazard functions, quantile function, moments, incomplete moments, generating functions, mean deviations, Bonferroni and Lorenz curves and order statistics are presented. For the GEMW, we also present Renyi entropy, estimation of parameters by using method of maximum likelihood, asymptotic confidence intervals and applications using real data.
Author: N. Balakrishnan
Publisher: Springer Science & Business Media
ISBN: 0387096140
Category : Mathematics
Languages : en
Pages : 714
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Book Description
Along with a review of general developments relating to bivariate distributions, this volume also covers copulas, a subject which has grown immensely in recent years. In addition, it examines conditionally specified distributions and skewed distributions.
Author: Horst Rinne
Publisher: CRC Press
ISBN: 1420087444
Category : Business & Economics
Languages : en
Pages : 812
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Book Description
The Most Comprehensive Book on the SubjectChronicles the Development of the Weibull Distribution in Statistical Theory and Applied StatisticsExploring one of the most important distributions in statistics, The Weibull Distribution: A Handbook focuses on its origin, statistical properties, and related distributions. The book also presents various ap
Author: John I. McCool
Publisher: John Wiley & Sons
ISBN: 1118351983
Category : Technology & Engineering
Languages : en
Pages : 366
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Book Description
Understand and utilize the latest developments in Weibull inferential methods While the Weibull distribution is widely used in science and engineering, most engineers do not have the necessary statistical training to implement the methodology effectively. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data. The author explains the use of the Weibull distribution and its statistical and probabilistic basis, providing a wealth of material that is not available in the current literature. The book begins by outlining the fundamental probability and statistical concepts that serve as a foundation for subsequent topics of coverage, including: • Optimum burn-in, age and block replacement, warranties and renewal theory • Exact inference in Weibull regression • Goodness of fit testing and distinguishing the Weibull from the lognormal • Inference for the Three Parameter Weibull Throughout the book, a wealth of real-world examples showcases the discussed topics and each chapter concludes with a set of exercises, allowing readers to test their understanding of the presented material. In addition, a related website features the author's own software for implementing the discussed analyses along with a set of modules written in Mathcad®, and additional graphical interface software for performing simulations. With its numerous hands-on examples, exercises, and software applications, Using the Weibull Distribution is an excellent book for courses on quality control and reliability engineering at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for engineers, scientists, and business analysts who gather and interpret data that follows the Weibull distribution
Author: Tao Yang
Publisher:
ISBN:
Category : Distribution (Probability theory)
Languages : en
Pages : 62
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Book Description
Author's abstract: In this thesis, the generalized inverseWeibull distribution including the proportional reverse hazard and Kumasraswamy generalized inverse Weibull distributions are presented. Properties of these distributions including the behavior of the hazard and reverse hazard functions, moments, coe_cients of variation, skewness, and kurtosis, _entropy, generalized entropy, Fisher information matrix, informational energy are studied. Estimates of the model parameters via several methods including maximum likelihood (MLE), and method of moments (MME) are presented.
