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Mathematical statistics; Data processing

Most popular at the top

  • Data Analysis and Graphics Using Rby John Maindonald; W. John Braun

    Cambridge University Press 2010; US$ 76.00

    Hands-on guide to the R system for data analysis for scientists, students and practising statisticians. more...

  • R Graphs Cookbookby Jaynal Abedin; Hrishi V. Mittal

    Packt Publishing 2014; US$ 32.99

    Targeted at those with an existing familiarity with R programming, this practical guide will appeal directly to programmers interested in learning effective data visualization techniques with R and a wide-range of its associated libraries. more...

  • Handbook of Statisticsby Marepalli B. Rao; C.R. Rao

    Elsevier Science 2014; US$ 250.00

    R is open source statistical computing software. Since the R core group was formed in 1997, R has been extended by a very large number of packages with extensive documentation along with examples freely available on the internet. It offers a large number of statistical and numerical methods and graphical tools and visualization of extraordinarily... more...

  • The Basics of S-PLUSby Andreas Krause; Melvin Olson

    Springer-Verlag New York Inc 2006; US$ 169.00

    Teaches the basics of S-PLUS Version 7.0 for people with little computing or statistical knowledge. This book demonstrates the important concepts of S-PLUS and R, its companion in implementing the S language. It also offers a guided tour of interactive computing, data exploration, and statistical analysis. more...

  • Data Manipulation with Rby Phil Spector

    Springer 2008; US$ 79.95

    Everyone using R needs to work with data, data almost always comes from an external source that has to be imported into R. The tasks covered in this book are essential tasks in R. more...

  • Dynamic Linear Models with Rby Patrizia Campagnoli; Sonia Petrone; Giovanni Petris

    Springer 2009; US$ 79.95

    State space models have gained tremendous popularity in as disparate fields as engineering, economics, genetics and ecology. Introducing general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. It illustrates the fundamental steps needed to use dynamic linear models in practice, using R package. more...

  • Behavioral Research Data Analysis with Rby Yuelin Li; Jonathan Baron

    Springer 2011; US$ 59.95

    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. The authors aim primarily to help practitioners of behavioral research make the transition to R. The focus is to provide practical advice on some of the widely-used statistical... more...

  • R by Exampleby Jim Albert; Maria Rizzo

    Springer 2012; US$ 64.95

    R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. 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... more...

  • Competing Risks and Multistate Models with Rby Jan Beyersmann; Arthur Allignol; Martin Schumacher

    Springer 2011; US$ 59.95

    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). Both R and multistate methods are promoted... more...

  • Theory and Applications of Gaussian Quadrature Methodsby Narayan Kovvali

    Morgan & Claypool Publishers 2011; US$ 35.00

    Gaussian quadrature is a powerful technique for numerical integration that falls under the broad category of spectral methods. The purpose of this work is to provide an introduction to the theory and practice of Gaussian quadrature. We study the approximation theory of trigonometric and orthogonal polynomials and related functions and examine the analytical... more...