Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization Paperback - 2019
by Matt Wiley; Joshua F. Wiley
From the rear cover
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
Details
- Title Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization
- Author Matt Wiley; Joshua F. Wiley
- Binding Paperback
- Pages 638
- Volumes 1
- Language ENG
- Publisher Apress
- Date 2019-02-21
- Illustrated Yes
- Features Bibliography, Illustrated
- ISBN 9781484228715 / 1484228715
- Weight 2.48 lbs (1.12 kg)
- Dimensions 10 x 7 x 1.33 in (25.40 x 17.78 x 3.38 cm)
- Dewey Decimal Code 005.11
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