相關主題
商品描述
This book offers a comprehensive exploration of popular continuous distribution families, including Exponentiated, Beta, Kumaraswamy, T-X, and Transmuted. It details methods for developing new distribution families, their properties, and inference. Practical applications of the members of families are enhanced by R code for maximum likelihood estimation.
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.
商品描述(中文翻譯)
這本書全面探討了流行的連續分佈族，包括指數分佈（Exponentiated）、貝塔分佈（Beta）、庫馬拉斯瓦米分佈（Kumaraswamy）、T-X 分佈和轉換分佈（Transmuted）。書中詳細介紹了開發新分佈族的方法、它們的性質以及推斷。透過 R 語言的最大似然估計（maximum likelihood estimation）程式碼，增強了這些分佈族成員的實際應用。
這本資源對於分佈理論及相關領域的研究是無價的，提供了一個整合的知識基礎，並促進了新分佈族及其成員的發展。這本書的重要性在於其對當代分佈族的整合和全面處理，這些分佈族已經徹底改變了現實數據的擬合方式。書中將貝塔分佈、T-X 分佈和轉換分佈等族的機制、性質和推斷方法集中在一處。書中討論了累積分佈函數（cumulative distribution function）、可靠性分析（reliability analysis）和最大似然估計的關鍵主題，以便讀者學習。此外，包含的 R 語言程式碼為最大似然估計提供了實用的應用價值。更進一步，這本書積極鼓勵新分佈族及其成員的開發，促進了該領域的創新。其對各種分佈族及其性質的詳細覆蓋，加上易於理解的解釋，使其成為既有研究者和新進分佈理論學者的重要資產。
目標讀者包括研究生和碩士生統計學學生、分佈理論的研究員，以及數學和物理等相關領域的讀者。
作者簡介
Muhammad Qaiser Shahbaz is Professor of Statistics at King Abdulaziz University, Jeddah, Saudi Arabia. He is a well-established researcher in the field of statistics with significant contributions to academic literature and book publications. His work focuses mainly on Statistics, and he works in areas including Ordered Random Variables and Multivariate Techniques. He has also published works on statistical theory and applications.
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.
作者簡介(中文翻譯)
穆罕默德·凱瑟爾·沙巴茲（Muhammad Qaiser Shahbaz）是沙烏地阿拉伯吉達的阿卜杜勒阿齊茲國王大學統計學教授。他在統計學領域是一位知名的研究者，對學術文獻和書籍出版有著重要的貢獻。他的研究主要集中在統計學，並涉及有序隨機變數和多變量技術等領域。他還發表了有關統計理論和應用的作品。
薩曼·哈尼夫·沙巴茲（Saman Hanif Shahbaz）在沙烏地阿拉伯吉達的阿卜杜勒阿齊茲國王大學科學院統計系工作。他是一位活躍的統計方法和分析研究者，專注於統計學、數據分析和統計估計方法。
穆罕默德·阿哈桑烏拉（Mohammad Ahsanullah）是美國新澤西州勞倫斯維爾的萊德大學名譽教授。他曾在管理科學系任職。他是美國統計協會的會士及終身會員，也是英國皇家統計學會的會士。
