Limit search to available items
Record 2 of 266
Previous Record Next Record
Book Cover
E-book
Author Wiley, Matt, author.

Title Advanced R statistical programming and data models : analysis, machine learning, and visualization / Matt Wiley, Joshua F. Wiley
Published [Berkeley, CA] : Apress, 2019

Copies

Description 1 online resource (xx, 638 pages) : illustrations (some color)
Contents Univariate data visualization -- Multivariate data visualization -- GLM 1 -- GLM 2 -- GAMs -- ML: introduction -- ML: unsupervised -- ML: supervised -- Missing data -- GLMMs: introduction -- GLMMs: linear -- GLMMs: advanced -- Modeling IIV
Summary Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and concludes with a case study. Written by Matt and Joshua F. Wiley, Advanced R Statistical Programming and Data Models shows you how to conduct data analysis using the popular R language. You'll delve into the preconditions or hypothesis for various statistical tests and techniques and work through concrete examples using R for a variety of these next-level analytics. This is a must-have guide and reference on using and programming with the R language. You will: Conduct advanced analyses in R including: generalized linear models, generalized additive models, mixed effects models, machine learning, and parallel processing Carry out regression modeling using R data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R including parallel processing, dimension reduction, and feature selection and classification Address missing data using multiple imputation in R Work on factor analysis, generalized linear mixed models, and modeling intraindividual variability
Bibliography Includes bibliographical references and index
Notes Online resource; title from PDF title page (SpringerLink, viewed February 28, 2019)
Subject R (Computer program language)
Statistics -- Data processing.
Mathematical statistics -- Data processing.
Mathematical statistics -- Data processing
R (Computer program language)
Statistics -- Data processing
Form Electronic book
Author Wiley, Joshua F., author.
ISBN 9781484228722
1484228723