Statistical Theory & Methods

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Handbook of Quantile Regression


Roger Koenker, Victor Chernozhukov, Xuming He, Limin Peng
October 25, 2017

Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that mini...

Adaptive Survey Design


Barry Schouten, Andy Peytchev, James Wagner
August 4, 2017

Adaptive survey designs (ASDs) provide a framework for data-driven tailoring of data collection procedures to different sample members, often for cost and bias reduction. People vary in how likely they are to respond and in how they respond. This variation leads to opportunities to selectively deplo...

Statistical and Machine-Learning Data Mining, Third Edition: Techniques for Better Predictive Modeling and Analysis of Big Data, Third Edition


Bruce Ratner
June 1, 2017

The third edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. is a compilation of new and creative d...

Mathematical Theory of Bayesian Statistics

Sumio Watanabe
April 20, 2018

Mathematical Theory of Bayesian Statistics introduces the mathematical foundation of Bayesian inference which is well-known to be more accurate in many real-world problems than the maximum likelihood method. Recent research has uncovered several mathematical laws in Bayesian statistics, by which...

An Introduction to Generalized Linear Models, Fourth Edition

Annette J. Dobson, Adrian G. Barnett
April 13, 2018

An Introduction to Generalized Linear Models, Fourth Edition provides a cohesive framework for statistical modelling, with an emphasis on numerical and graphical methods. This new edition of a bestseller has been updated with new sections on non-linear associations, strategies for model selection,...

Probabilistic Foundations of Statistical Network Analysis

Harry Crane
April 09, 2018

Probabilistic Foundations of Statistical Network Analysis presents a fresh and insightful perspective on the fundamental tenets and major challenges of modern network analysis. Its lucid exposition provides necessary background for understanding the essential ideas behind exchangeable and dynamic...

Analysis of Correlated Data with SAS and R, Fourth Edition

Mohamed M. Shoukri
April 02, 2018

Analysis of Correlated Data with SAS and R: 4th edition presents an applied treatment of recently developed statistical models and methods for the analysis of hierarchical binary, count and continuous response data. It explains how to use procedures in SAS and packages in R for exploring data,...

Bayesian Methods for Repeated Measures

Lyle D. Broemeling
April 01, 2018

Analyze Repeated Measures Studies Using Bayesian Techniques Going beyond standard non-Bayesian books, Bayesian Methods for Repeated Measures presents the main ideas for the analysis of repeated measures and associated designs from a Bayesian viewpoint. It describes many inferential methods for...

Linear Models and the Relevant Distributions and Matrix Algebra

David A. Harville
March 13, 2018

Linear Models and the Relevant Distributions and Matrix Algebra provides in-depth and detailed coverage of the use of linear statistical models as a basis for parametric and predictive inference. It can be a valuable reference, a primary or secondary text in a graduate-level course on linear models...

Missing and Modified Data in Nonparametric Estimation: With R Examples

Sam Efromovich
March 12, 2018

This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random,...

The Mata Book: A Book for Serious Programmers and Those Who Want to Be

William Gould
February 26, 2018

The Mata Book: A Book for Serious Programmers and Those Who Want to Be is the book that Stata programmers have been waiting for. Mata is a serious programming language for developing small- and large-scale projects and for adding features to Stata. What makes Mata serious is that it provides...

Statistics in the Health Sciences: Theory, Applications, and Computing

Albert Vexler, Alan Hutson
February 07, 2018

"This very informative book introduces classical and novel statistical methods that can be used by theoretical and applied biostatisticians to develop efficient solutions for real-world problems encountered in clinical trials and epidemiological studies. The authors provide a detailed discussion of...

Chain Event Graphs

Rodrigo A. Collazo, Christiane Goergen, Jim Q. Smith
January 31, 2018

   Written by some major contributors to the development of this class of graphical models, Chain Event Graphs introduces a viable and straightforward new tool for statistical inference, model selection and learning techniques. The book extends established technologies used in the study of...

Theory of Stochastic Objects: Probability, Stochastic Processes and Inference

Athanasios Christou Micheas
January 29, 2018

This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks;...

A Course in Item Response Theory and Modeling with Stata

Tenko Raykov, George A. Marcoulides
January 25, 2018

Over the past several decades, item response theory (IRT) and item response modeling (IRM) have become increasingly popular in the behavioral, educational, social, business, marketing, clinical, and health sciences. In this book, Raykov and Marcoulides begin with a nontraditional approach to IRT...