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Modern Data Science with R

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Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
February 2, 2017

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programmi...

Generalized Additive Models: An Introduction with R, Second Edition

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Simon N. Wood
June 6, 2017

The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary bac...

Testing R Code

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Richard Cotton
January 19, 2017

Learn how to write R code with fewer bugs. The problem with programming is that you are always one typo away from writing something silly. Likewise with data analysis, a small mistake in your model can lead to a big mistake in your results. Combining the two disciplines means that it is all too easy...

Exploratory Data Analysis with MATLAB, Third Edition

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Wendy L. Martinez, Angel R. Martinez, Jeffrey Solka
June 1, 2017

Praise for the Second Edition:"The authors present an intuitive and easy-to-read book. … accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB."—Adolfo Alvarez Pinto, International Statistical Review "Prac...

Asymptotic Analysis of Mixed Effects Models: Theory, Applications, and Open Problems

Jiming Jiang
June 15, 2017

Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice....

Data Analysis Using Hierarchical Generalized Linear Models with R

Youngjo Lee, Lars Ronnegard, Maengseok Noh
June 15, 2017

Since their introduction, hierarchical generalized linear models (HGLMs) have proven useful in various fields by allowing random effects in regression models. Interest in the topic has grown, and various practical analytical tools have been developed. This book summarizes developments within the...

Generalized Additive Models: An Introduction with R, Second Edition

Simon N. Wood
June 06, 2017

The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary...

Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood, Second Edition

Youngjo Lee, John A. Nelder, Yudi Pawitan
June 05, 2017

This is the second edition of a monograph on generalized linear models with random effects that extends the classic work of McCullagh and Nelder. It has been thoroughly updated, with around 80 pages added, including new material on the extended likelihood approach that strengthens the theoretical...

Exploratory Data Analysis with MATLAB, Third Edition

Wendy L. Martinez, Angel R. Martinez, Jeffrey Solka
June 01, 2017

Praise for the Second Edition:"The authors present an intuitive and easy-to-read book. … accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB."—Adolfo Alvarez Pinto, International Statistical Review "...

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

Bruce Ratner
June 01, 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...

Modern Statistics for the Social and Behavioral Sciences: A Practical Introduction, Second Edition

Rand Wilcox
May 30, 2017

Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences provides a two-semester, graduate-level introduction to basic statistical techniques that takes into account recent advances and insights that are typically ignored in an introductory course. Hundreds of journal...

Flexible Regression and Smoothing: Using GAMLSS in R

Mikis D. Stasinopoulos, Robert A. Rigby, Gillian Z. Heller, Vlasios Voudouris, Fernanda De Bastiani
May 08, 2017

This book is about learning from data using the Generalized Additive Models for Location, Scale and Shape (GAMLSS). GAMLSS extends the Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) to accommodate large complex datasets, which are increasingly prevalent. GAMLSS allows any...

Exploratory Multivariate Analysis by Example Using R, Second Edition

Francois Husson, Sebastien Le, Jérôme Pagès
April 25, 2017

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when...

Quality Management for Organizations Using Lean Six Sigma Techniques

Erick Jones
March 31, 2017

The next step in the evolution of the organizational quality field, Lean Six Sigma (LSS) has come of age. However, many challenges to using LSS in lieu of, in conjunction with, or integrated with other quality initiatives remain. An update on the current focus of quality management, Quality...

Change-Point Analysis in Nonstationary Stochastic Models

Boris Brodsky
March 23, 2017

This book covers the development of methods for detection and estimation of changes in complex systems. These systems are generally described by nonstationary stochastic models, which comprise both static and dynamic regimes, linear and nonlinear dynamics, and constant and time-variant structures...

Modern Data Science with R

Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
February 02, 2017

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical...

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