This book is a tribute to Professor A. K. Md. Ehsanes Saleh, a distinguished figure in the field of statistics known for his pioneering work, including the development of the "Preliminary Test Approach to Shrinkage Estimation". Although Professor Saleh passed away in September 2023, his legacy will live on through this special volume that explores penalized approaches for statistical analysis and recent developments in shrinkage methods. Covering regression modeling, robust estimation, mac...

Rank-Based Methods for Shrinkage and SelectionA practical and hands-on guide to the theory and methodology of statistical estimation based on rankRobust statistics is an important field in contemporary mathematics and applied statistical methods. Rank-Based Methods for Shrinkage and Selection: With Application to Machine Learning describes techniques to produce higher quality data analysis in shrinkage and subset selection to obtai...

Multivariate statistical analysis has undergone a rich and varied evolution during the latter half of the 20th century. Academics and practitioners have produced much literature with diverse interests and with varying multidisciplinary knowledge on different topics within the multivariate domain. Due to multivariate algebra being of sustained interest and being a continuously developing field, its appeal breaches laterally across multiple disciplines to act as a catalyst for contemporary a...

This book summarizes the results of various models under normal theory with a brief review of the literature. Statistical Inference for Models with Multivariate t-Distributed Errors:Includes a wide array of applications for the analysis of multivariate observationsEmphasizes the development of linear statistical models with applications to engineering, the physical sciences, and mathematicsContains an up-to-date bibliography featuring the latest t...

A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applicationsTheory of Ridge Regression Estimation with Applications offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains ...

This reference manual for the OpenStat software, an open-source software developed by William Miller, covers a broad spectrum of statistical methods and techniques. A unique feature is its compatibility with many other statistical programs. OpenStat users are researchers and students in the social sciences, education, or psychology, who benefit from the hands on approach to Statistics. During and upon completion of courses in Statistics or measurement, students and future researchers need ...

The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments.The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 deal...

Based on a course in the theory of statistics this text concentrates on what can be achieved using the likelihood/Fisherian method of taking account of uncertainty when studying a statistical problem. It takes the concept ot the likelihood as providing the best methods for unifying the demands of statistical modelling and the theory of inference. Every likelihood concept is illustrated by realistic examples, which are not compromised by computational problems. Examples range from a simile ...

Introduction to Functional Data Analysis provides a concise textbook introduction to the field. It explains how to analyze functional data, both at exploratory and inferential levels. It also provides a systematic and accessible exposition of the methodology and the required mathematical framework.The book can be used as textbook for a semester-long course on FDA for advanced undergraduate or MS statistics majors, as well as for MS and PhD students in other disciplines, including a...

Most behavioral scientists know two important concepts -- how to analyze continuous data from randomly assigned treatment groups of subjects and how to assess practice effects for a single group of subjects given a constant treatment at each of several stages of practice. However, except in the case of the repeated measures Latin square design, researchers are not facile in analyzing data from different subjects receiving different treatments at various times in an experiment. This book he...

This complete resource on the theory and applications of reliability engineering, probabilistic models and risk analysis consolidates all the latest research, presenting the most up-to-date developments in this field.With comprehensive coverage of the theoretical and practical issues of both classic and modern topics, it also provides a unique commemoration to the centennial of the birth of Boris Gnedenko, one of the most prominent reliability scientists of the twentieth century.

Methods for estimating sparse and large covariance matricesCovariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance ma...