
Univariate Families of Distributions
Description
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This resource is invaluable for studies into distribution theory and related fields, providing a consolidated knowledge base and facilitating the development of novel families of distributions and their members. The book's significance lies in its consolidated and comprehensive treatment of contemporary distribution families, which have revolutionized real-life data fitting. The book presents mechanisms, properties, and inferential methods for families like Beta, T-X, and Transmuted families in one place. Key topics on cumulative distribution function, reliability analysis, and maximum likelihood estimation are discussed for the reader's learning. The inclusion of R codes for maximum likelihood estimation offers practical utility in applying these distributions. Furthermore, the book actively encourages the development of new distribution families and members, fostering innovation in the field. Its detailed coverage of various families and their properties, coupled with accessible explanations, makes it a crucial asset for both established researchers and those new to distribution theory.
The target audience includes graduate and postgraduate statistics students, research fellows in distribution theory, and readers in allied fields like mathematics and physics.
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Saman Hanif Shahbaz works at the Department of Statistics, Faculty of Sciences, King Abdulaziz University, Jeddah, Saudi Arabia. He is an active researcher in statistical methods and analysis, with a focus on statistics, data analysis, and statistical estimation methods.
Mohammad Ahsanullah is Professor Emeritus at Rider University, Lawrenceville, New Jersey, USA. He has previously served in the Department of Management Sciences. He is a Fellow and life member of the American Statistical Association and a Fellow of the Royal Statistical Society.
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