XploRe: An Interactive Statistical Computing Environment

XploRe: An Interactive Statistical Computing Environment
Author: Wolfgang Härdle
Publisher: Springer Science & Business Media
Total Pages: 406
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461242142

This book describes an interactive statistical computing environment called 1 XploRe. As the name suggests, support for exploratory statistical analysis is given by a variety of computational tools. XploRe is a matrix-oriented statistical language with a comprehensive set of basic statistical operations that provides highly interactive graphics, as well as a programming environ ment for user-written macros; it offers hard-wired smoothing procedures for effective high-dimensional data analysis. Its highly dynamic graphic capa bilities make it possible to construct student-level front ends for teaching basic elements of statistics. Hot keys make it an easy-to-use computing environment for statistical analysis. The primary objective of this book is to show how the XploRe system can be used as an effective computing environment for a large number of statistical tasks. The computing tasks we consider range from basic data matrix manipulations to interactive customizing of graphs and dynamic fit ting of high-dimensional statistical models. The XploRe language is similar to other statistical languages and offers an interactive help system that can be extended to user-written algorithms. The language is intuitive and read ers with access to other systems can, without major difficulty, reproduce the examples presented here and use them as a basis for further investigation.

XploRe

XploRe
Author:
Publisher:
Total Pages: 0
Release: 2000
Genre:
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Introductory Statistics with R

Introductory Statistics with R
Author: Peter Dalgaard
Publisher: Springer Science & Business Media
Total Pages: 370
Release: 2008-06-27
Genre: Mathematics
ISBN: 0387790543

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.

Modern Applied Statistics with S

Modern Applied Statistics with S
Author: W.N. Venables
Publisher: Springer Science & Business Media
Total Pages: 501
Release: 2013-03-09
Genre: Mathematics
ISBN: 0387217061

A guide to using S environments to perform statistical analyses providing both an introduction to the use of S and a course in modern statistical methods. The emphasis is on presenting practical problems and full analyses of real data sets.

Software for Data Analysis

Software for Data Analysis
Author: John Chambers
Publisher: Springer Science & Business Media
Total Pages: 515
Release: 2008-06-14
Genre: Computers
ISBN: 0387759360

John Chambers turns his attention to R, the enormously successful open-source system based on the S language. His book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated. This is the only advanced programming book on R, written by the author of the S language from which R evolved.

Elements of Computational Statistics

Elements of Computational Statistics
Author: James E. Gentle
Publisher: Springer Science & Business Media
Total Pages: 427
Release: 2006-04-18
Genre: Computers
ISBN: 0387216111

Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books

Modern Applied Statistics with S-PLUS

Modern Applied Statistics with S-PLUS
Author: W.N. Venables
Publisher: Springer Science & Business Media
Total Pages: 508
Release: 2013-04-17
Genre: Computers
ISBN: 1475731213

This best-selling guide has been completely updated to present the newest features of S-PLUS 5.0, and includes the very latest computationally-intensive methods and techniques. In addition, extensive software libraries, data sets, and complements will be available online. "the task the authors have undertaken is challenginggetting new S/S-Plus users to quickly learn the fundamentals of the language and presenting a modern approach to data analysis through numerous examples from many areas of statistics. They succeed in this" TECHNOMETRICS

Numerical Linear Algebra for Applications in Statistics

Numerical Linear Algebra for Applications in Statistics
Author: James E. Gentle
Publisher: Springer Science & Business Media
Total Pages: 229
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461206235

Accurate and efficient computer algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Regardless of the software system used, the book describes and gives examples of the use of modern computer software for numerical linear algebra. It begins with a discussion of the basics of numerical computations, and then describes the relevant properties of matrix inverses, factorisations, matrix and vector norms, and other topics in linear algebra. The book is essentially self- contained, with the topics addressed constituting the essential material for an introductory course in statistical computing. Numerous exercises allow the text to be used for a first course in statistical computing or as supplementary text for various courses that emphasise computations.

Smoothing Methods in Statistics

Smoothing Methods in Statistics
Author: Jeffrey S. Simonoff
Publisher: Springer Science & Business Media
Total Pages: 349
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461240263

Focussing on applications, this book covers a very broad range, including simple and complex univariate and multivariate density estimation, nonparametric regression estimation, categorical data smoothing, and applications of smoothing to other areas of statistics. It will thus be of particular interest to data analysts, as arguments generally proceed from actual data rather than statistical theory, while the "Background Material" sections will interest statisticians studying the field. Over 750 references allow researchers to find the original sources for more details, and the "Computational Issues" sections provide sources for statistical software that use the methods discussed. Each chapter includes exercises with a heavily computational focus based upon the data sets used in the book, making it equally suitable as a textbook for a course in smoothing.

Modern Applied Statistics with S-PLUS

Modern Applied Statistics with S-PLUS
Author: William N. Venables
Publisher: Springer Science & Business Media
Total Pages: 562
Release: 2013-11-11
Genre: Mathematics
ISBN: 1475727194

A guide to using the power of S-PLUS to perform statistical analyses, providing both an introduction to the program and a course in modern statistical methods. Readers are assumed to have a basic grounding in statistics, thus the book is intended for would-be users, as well as students and researchers using statistics. Throughout, the emphasis is on presenting practical problems and full analyses of real data sets, with many of the methods discussed being modern approaches to topics such as linear and non-linear regression models, robust and smooth regression methods, survival analysis, multivariate analysis, tree-based methods, time series, spatial statistics, and classification. This second edition is intended for users of S-PLUS 3.3, or later, and covers both Windows and UNIX. It treats the recent developments in graphics and new statistical functionality, including bootstraping, mixed effects linear and non-linear models, factor analysis, and regression with autocorrelated errors. The authors have written several software libraries which enhance S-PLUS, and these, plus all the datasets used, are available on the Internet.