Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization. Matt Wiley, Joshua F. Wiley
Advanced-R-Statistical.pdf
ISBN: 9781484228715 | 638 pages | 16 Mb
- Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization
- Matt Wiley, Joshua F. Wiley
- Page: 638
- Format: pdf, ePub, fb2, mobi
- ISBN: 9781484228715
- Publisher: Apress
Download new books nook Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization (English literature)
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. What You’ll Learn 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 Who This Book Is For Working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to use R to perform more advanced analytics. Particularly, researchers and data analysts in the social sciences may benefit from these techniques. Additionally, analysts who need parallel processing to speed up analytics are given proven code to reduce time to result(s).
Advanced R Statistical Programming and Data Models - Analysis
Advanced R Statistical Programming and Data Models. Analysis, Machine Learning, and Visualization. Autoren: Wiley, Matt, Wiley, Joshua F. Demonstrates
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What You'll Learn Conduct advanced analyses in R including: generalized out regression modeling using R data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R Advanced R Statistical Programming and Data Models: Analysis, Machine
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Advanced R Statistical Programming and Data Models - Springer
All errors and omissions excepted. M. Wiley, J.F. Wiley. Advanced R Statistical Programming and Data Models. Analysis, Machine Learning, and Visualization.
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Advanced R Statistical Programming and Data Models: Analysis
Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Carry out regression modeling using R data visualization, linear and Handle machine learning using R including parallel processing, dimension
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