Advanced R Statistical Programming and Data Models
PDF
 eBook:Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization
 Author:Matt Wiley, Joshua F. Wiley
 Edition:1st ed. edition
 Categories:
 Data:February 21, 2019
 ISBN:1484228715
 ISBN13:9781484228715
 Language:English
 Pages:638 pages
 Format:PDF
Written by Matt and Joshua F. Wiley, Advanced R Statistical Programming and Data Modelsshows 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 nextlevel analytics. This is a musthave 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
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).

Content
Chapter 2: Multivariate Data Visualization
Chapter 3: GLM 1
Chapter 4: GLM 2
Chapter 5: GAMs
Chapter 6: ML: Introduction
Chapter 7: ML: Unsupervised
Chapter 8: ML: Supervised
Chapter 9: Missing Data
Chapter 10: GLMMs: Introduction
Chapter 11: GLMMs: Linear
Chapter 12: GLMMs: Advanced
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