Bücher der Reihe Use R!

This book provides a narrative of how R can be useful in the analysis of public administration, public policy, and political science data specifically, in addition to the social sciences more broadly.

This book provides a comprehensive introduction to performing meta-analysis using the statistical software R. It is intended for quantitative researchers and students in the medical and social sciences who wish to learn how to perform meta-analysis with R. multivariate meta-analysis, network meta-analysis;

This book provides an introduction to multistate event history analysis. It is the subsample of the German Life History Survey, which was also used by Blossfeld and Rohwer in their popular textbook on event history modeling.

Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data.

Functional and Phylogenetic Ecology in R is designed to teach readers to use R for phylogenetic and functional trait analyses. Researchers getting started in R can use this volume as a step-by-step entryway into phylogenetic and functional analyses for ecology in R.

Bayesian Networks in R with Applications in Systems Biology is unique as it introduces the reader to the essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R.

Many of the commonly used methods for modeling and fitting psychophysical data are special cases of statistical procedures of great power and generality, notably the Generalized Linear Model (GLM).

This updated second edition includes material on interfacing R with other computer languages such as C. It reflects the increasing availability of molecular and genetic databases which allow biologists to pursue new issues such as molecular evolution patterns.

Business Analytics for Managers helps readers extract knowledge and actionable insight from real business data. The text emphasizes data-driven thinking and provides a quick-start guide to one of the most powerful software solutions available.

The focus on doing data mining rather than just reading about data mining is refreshing.The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment.

This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool.

R functions are presented in the context of interesting applications with real data. The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics.

This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models).

This volume provides user-friendly software and a GUI package to assist with microarray data analysis in early drug development. Each methodological issue is illustrated using real-world examples of early drug development dose-response microarray experiments.

This book presents the statistical analysis of compositional data sets, i.e., data in percentages, proportions, concentrations, etc.

With Rcpp, the transfer of data between R and C++ is nearly seamless, and high-performance statistical computing is finally accessible to most R users. Rcpp permits users to pass scalars, vectors, matrices, list or entire R objects back and forth between R and C++ with ease.

As an area of statistical application, environmental epidemiology and more speci cally, the estimation of health risk associated with the exposure to - vironmental agents, has led to the development of several statistical methods and software that can then be applied to other scienti c areas.

This book aims to explain how to use R to perform morphometrics. Although there is an increasing number of computer applications that perform morphometrics, using R has several advantages that confer to users considerable power and possible new horizons in a world that requires rapid adaptability.

This book contains information on how to tackle many important problems using a multiscale statistical approach. It focuses on how to use multiscale methods and discusses methodological and applied considerations.

This environment should be such that one can: write short scripts to de?ne a Bayesian model use or write functions to summarize a posterior distribution use functions to simulate from the posterior distribution construct graphs to illustrate the posterior inference An environment that meets these requirements is the R system.

Once the model has been introduced it is used to generate synthetic data, using R code, and these generated data are then used to estimate its parameters. This sequence enhances understanding of both the time series model and the R function used to fit the model to data.

This richly illustrated book describes the use of interactive and dynamic graphics as part of multidimensional data analysis. A variety of plots and interaction methods are used in each analysis, often starting with brushing linked low-dimensional views and working up to manual manipulation of tours of several variables.

Bioconductor software has become a standard tool for the analysis and comprehension of data from high-throughput genomics experiments. (6) gene set enrichment analysis. Each chapter of this book describes an analysis of real data using hands-on example driven approaches.

Along with the ongoing developments of graphical models, a number of different graphical modeling software programs have been written over the years. Topics covered in the seven chapters include graphical models for contingency tables, Gaussian and mixed graphical models, Bayesian networks and modeling high dimensional data.

Written by the author of the lattice system, this book describes lattice in considerable depth, beginning with the essentials and systematically delving into specific low levels details as necessary. No prior experience with lattice is required to read the book, although basic familiarity with R is assumed.

Our aim is to give a practical and theoretical account of how to solve a large variety of differential equations, comprising ordinary differential equations, initial value problems and boundary value problems, differential algebraic equations, partial differential equations and delay differential equations.

Six Sigma has arisen in the last two decades as a breakthrough Quality Management Methodology. The aim of this book is to show how R can be used as the software tool in the development of Six Sigma projects. The book includes a gentle introduction to Six Sigma and a variety of examples showing how to use R within real situations.