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 ...

Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share n...

Making good decisions under conditions of uncertainty - which is the norm - requires a sound appreciation of the way random chance works. As analysis and modelling of most aspects of the world, and all measurement, are necessarily imprecise and involve uncertainties of varying degrees, the understanding and management of probabilities is central to much work in the sciences and economics.In this Very Short Introduction, John Haigh introduces the ideas of probability and different philosoph...

APPROACHES TO QUANTITATIVE RESEARCH is designed for both undergraduate and postgraduate business students who are planning to undertake a research project or dissertation. Due to a lack of formal research training and experience, students can find completing research projects a daunting task. This, coupled with a fear of statistics, can culminate in quite an overwhelming experience for many students. Therefore, APPROACHES TO QUANTITATIVE RESEARCH takes a practical approach to quantitative ...

A new edition of the definitive guide to logistic regression modeling for health science and other applicationsThis thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables.Applied Logistic Regression, Third Edition emphasizes applications in t...

Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques.This new fourth edition looks at recent techniques such as variational methods, Bayesian importance sampling, approximate Bayesian computation and Reversible Jump Markov Chain Monte Carlo (RJM...

The philosopher Cristina Bicchieri here develops her theory of social norms, most recently explained in her 2006 volume The Grammar of Society. Bicchieri challenges many of the fundamental assumptions of the social sciences. She argues that when it comes to human behavior, social scientists place too much stress on rational deliberation. In fact, many choices occur without much deliberation at all. Bicchieri's theory accounts for these automatic components of behavior, where indiv...

This textbook systematically presents fundamental methods of statistical analysis: from probability and statistical distributions, through basic concepts of statistical inference, to a collection of methods of analysis useful for scientific research. It is rich in tables, diagrams, and examples, in addition to theoretical justification of the methods of analysis introduced. Each chapter has a section entitled “Exercises and Problems” to accompany the text. There are altogether about 300 ex...