Statistical Theory of Inliers Models, Methods and Applications

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.