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:: 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...

Handbook of Approximate Bayesian Computation

Scott A. Sisson, Yanan Fan, Mark Beaumont
August 10, 2018

As the world becomes increasingly complex, so do the statistical models required to analyse the challenging problems ahead. For the very first time in a single volume, the Handbook of Approximate Bayesian Computation (ABC) presents an extensive overview of the theory, practice and application of...

Statistics in Engineering, Second Edition: With Examples in MATLAB and R

Andrew Metcalfe, Tony Greenfield
August 06, 2018

This is a textbook for an undergraduate course in statistics for engineers with a minimal calculus prerequisite. The second edition differs from existing books in three main aspects: it is the only introductory statistics textbook written for engineers that uses R throughout the text, there is an...

Survey Sampling

Arijit Chaudhuri
July 24, 2018

This venture aspires to be a mix of a textbook at the undergraduate and postgraduate levels and a monograph to catch the attention of researchers in theoretical and practical aspects of survey sampling at diverse levels demanding a comprehensive review of what useful materials have preceded, with...

Flexible Imputation of Missing Data, Second Edition

Stef van Buuren
July 16, 2018

Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, which are often not met in practice. Multiple imputation replaces each missing value by multiple plausible values. The variability between...

Multiple Imputation in Practice: With Examples Using IVEware

Trivellore Raghunathan, Patricia A. Berglund, Peter W. Solenberger
July 12, 2018

Multiple Imputation in Practice: With Examples Using IVEware provides practical guidance on multiple imputation analysis, from simple to complex problems using real and simulated data sets. Data sets from cross-sectional, retrospective, prospective and longitudinal studies, randomized clinical...

Large Covariance and Autocovariance Matrices

Arup Bose, Monika Bhattacharjee
July 03, 2018

Large Covariance and Autocovariance Matrices brings together a collection of recent results on sample covariance and autocovariance matrices in high-dimensional models and novel ideas on how to use them for statistical inference in one or more high-dimensional time series models. The prerequisites...

Bayesian Methods for Repeated Measures

Lyle D. Broemeling
June 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...

Graphics for Statistics and Data Analysis with R

Kevin J. Keen
May 18, 2018

Praise for the First Edition "The main strength of this book is that it provides a unified framework of graphical tools for data analysis, especially for univariate and low-dimensional multivariate data. In addition, it is clearly written in plain language and the inclusion of R code is...

Nonparametric Models for Longitudinal Data: With Implementation in R

Colin O. Wu, Xin Tian
May 15, 2018

Nonparametric Models for Longitudinal Data with Implementations in R presents a comprehensive summary of major advances in nonparametric models and smoothing methods with longitudinal data. It covers methods, theories, and applications that are particularly useful for biomedical studies in the era...

Multivariate Kernel Smoothing and Its Applications

José E. Chacón, Tarn Duong
May 08, 2018

Kernel smoothing has greatly evolved since its inception to become an essential methodology in the Data Science tool kit for the 21st century. Its widespread adoption is due to its fundamental role for multivariate exploratory data analysis, as well as the crucial role it plays in composite...

Handbook of Educational Measurement and Psychometrics Using R

Christopher D. Desjardins, Okan Bulut
May 02, 2018

Currently there are many introductory textbooks on educational measurement and psychometrics as well as R. However, there is no single book that covers important topics in measurement and psychometrics as well as their applications in R. The Handbook of Educational Measurement and Psychometrics...

Generalized Linear Models and Extensions: Fourth Edition

James W. Hardin, Joseph M. Hilbe
April 27, 2018

Generalized linear models (GLMs) extend linear regression to models with a non-Gaussian, or even discrete, response. GLM theory is predicated on the exponential family of distributions—a class so rich that it includes the commonly used logit, probit, and Poisson models. Although one can fit these...