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Exploratory Data Analysis Using R

Ronald K. Pearson
May 29, 2018

Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be found in data, and why it is important to find them. It also introduces the mechanics of using R to...

Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition

Andrew B. Lawson
May 24, 2018

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in...

Graphics for Statistics and Data Analysis with R, Second Edition

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...

R for Programmers: Quantitative Investment Applications

Dan Zhang
May 07, 2018

After the fundamental volume and the advanced technique volume, this volume focuses on R applications in the quantitative investment area. Quantitative investment has been hot for some years, and there are more and more startups working on it, combined with many other internet communities and...

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...

Self-Controlled Case Series Studies: A Modelling Guide with R

Paddy Farrington, Heather Whitaker, Yonas Ghebremichael Weldeselassie
May 02, 2018

Self-Controlled Case Series Studies: A Modelling Guide with R provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical technique for investigating associations between outcome events and time-varying exposures. The method only requires information...

Sufficient Dimension Reduction: Methods and Applications with R

Bing Li
May 01, 2018

Sufficient dimension reduction is a rapidly developing research field that has wide applications in regression diagnostics, data visualization, machine learning, genomics, image processing, pattern recognition, and medicine, because they are fields that produce large datasets with a large number of...

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...

A Gentle Introduction to Stata

Alan C. Acock
April 12, 2018

Alan C. Acock's A Gentle Introduction to Stata, Sixth Edition is aimed at new Stata users who want to become proficient in Stata. After reading this introductory text, new users will be able not only to use Stata well but also to learn new aspects of Stata. Acock assumes that the user is not...

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...

Bayesian Regression Modeling with INLA

Xiaofeng Wang, Yu Yue Ryan, Julian J. Faraway
February 22, 2018

This book addresses the applications of extensively used regression models under a Bayesian framework. It emphasizes efficient Bayesian inference through integrated nested Laplace approximations (INLA) and real data analysis using R. The INLA method directly computes very accurate approximations to...

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...

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