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

Advanced R Statistical Programming and Data Models Analysis, Machine Learning, and Visualization / by Matt Wiley, Joshua F. Wiley.

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...

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Bibliographic Details
Main Authors: Wiley, Matt (Author), Wiley, Joshua F. (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berkeley, CA : Apress : Imprint: Apress, 2019.
Edition:1st ed. 2019.
Series:Springer eBook Collection.
Subjects:
Programming languages (Electronic computers).
Computer programming.
Mathematical statistics.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
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.

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