Statistical Theory of Inliers
Models, Methods and Applications
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Beschreibung
This book presents a rigorous and comprehensive exploration of inlier-prone models, delving into their theoretical foundations and wide-ranging applications. Inliers—like outliers—represent atypical observations, but unlike outliers, they tend to appear in clusters rather than in isolation. Traditional statistical methods often overlook this phenomenon, necessitating the use of non-standard probability distributions, which is an emerging area of interest in statistical research.
Through a multidisciplinary lens, the book examines the presence and impact of inliers across various fields, including statistics, social sciences, survival analysis, and clinical research, while also extending their relevance to other disciplines. Beyond technical insights, it thoughtfully addresses academic significance, ethical considerations, and interdisciplinary connections, making it an indispensable resource for researchers, scholars, and practitioners seeking to deepen their understanding of inlier behavior and its implications.
This book presents a rigorous and comprehensive exploration of inlier-prone models, delving into their theoretical foundations and wide-ranging applications. Inliers—like outliers—represent atypical observations, but unlike outliers, they tend to appear in clusters rather than in isolation. Traditional statistical methods often overlook this phenomenon, necessitating the use of non-standard probability distributions, which is an emerging area of interest in statistical research.
Through a multidisciplinary lens, the book examines the presence and impact of inliers across various fields, including statistics, social sciences, survival analysis, and clinical research, while also extending their relevance to other disciplines. Beyond technical insights, it thoughtfully addresses academic significance, ethical considerations, and interdisciplinary connections, making it an indispensable resource for researchers, scholars, and practitioners seeking to deepen their understanding of inlier behavior and its implications.
Discusses inlier-prone models, its theory and applications, for the first time in a book form Presents theoretical models supported by natural examples and applications of order statistics theory Focuses on future research in the field with applications in data analytics and big data concepts
Autor*in
K. Muralidharan
Themen in »Statistical Theory of Inliers«
statistical inference inliers probability distributions order statistics masking and swamping effect likelihood estimation UMVU estimation test for mixing proportion survival estimation Bayes estimation censoring Gompertz inliers tests of hypothesis