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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...

Errors, Blunders, and Lies: How to Tell the Difference

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David Salsburg
April 19, 2017

We live in a world that is not quite "right." The central tenet of statistical inquiry is that Observation = Truth + Error because even the most careful of scientific investigations have always been bedeviled by uncertainty. Our attempts to measure things are plagued with small errors. Our attempt...

Bioassays with Arthropods, Third Edition

Jacqueline L. Robertson, Moneen Marie Jones, Efren Olguin, Brad Alberts
June 23, 2017

Imagine a statistics book for bioassays written by a statistician. Next, imagine a statistics book for bioassays written for a layman. Bioassays with Arthropods, Third Edition offers the best of both worlds by translating the terse, precise language of the statistician into language used by the...

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...

Computational Methods for Numerical Analysis with R

James P Howard, II
June 12, 2017

Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R code....

Clinical Trial Optimization Using R

Alex Dmitrienko, Erik Pulkstenis
June 12, 2017

Clinical Trial Optimization Using R explores a unified and broadly applicable framework for optimizing decision making and strategy selection in clinical development, through a series of examples and case studies. It provides the clinical researcher with a powerful evaluation paradigm, as well as...

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...

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...

Big Data Management and Processing

Kuan-Ching Li, Hai Jiang, Albert Y. Zomaya
May 25, 2017

From the Foreword: "Big Data Management and Processing is [a] state-of-the-art book that deals with a wide range of topical themes in the field of Big Data. The book, which probes many issues related to this exciting and rapidly growing field, covers processing, management, analytics, and...

Logistic Regression Models

Joseph M. Hilbe
May 25, 2017

Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures. Other topics discussed include panel, survey, skewed, penalized, and exact logistic models. The...

Algorithms for Next-Generation Sequencing

Wing-Kin Sung
May 24, 2017

Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before – as many as hundreds of millions of short reads in the course of a few days. But what are the best ways to deal with this flood of data? Algorithms for...

Spatial Data Quality: From Process to Decisions

Rodolphe Devillers, Helen Goodchild
May 24, 2017

Producing maps that depict the real world accurately has been a major concern of cartographers for centuries. This is especially true today as escalating access to geospatial data and the subsequent increase in user-generated content provided by Web 2.0 have significantly altered the typical...

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