Advanced R Statistical Programming and Data Models Analysis, Machine Learning, and Visualization /

• Main Authors: Wiley, Matt (Author, http://id.loc.gov/vocabulary/relators/aut), Wiley, Joshua F. (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berkeley, CA : Apress : Imprint: Apress, 2019.
• Edition: 1st ed. 2019.
• Subjects: Programming languages (Electronic computers).; Computer programming.; Mathematical statistics.; Programming Languages, Compilers, Interpreters.; Programming Techniques.; Probability and Statistics in Computer Science.

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 us...

Table of Contents:

• 1 Univariate Data Visualization
• 2 Multivariate Data Visualization
• 3 Generalized Linear Models 1
• 4 Generalized Linear Models 2
• 5 Generalized Additive Models
• 6 Machine Learning: Introduction
• 7 Machine Learning: Unsupervised
• 8 Machine Learning: Supervised
• 9 Missing Data
• 10 Generalized Linear Mixed Models: Introduction
• 11 Generalized Linear Mixed Models: Linear
• 12 Generalized Linear Mixed Models: Advanced
• 13 Modeling IIV
• Bibliography.