O'Reilly logo

Mastering Scientific Computing with R by Radia M. Johnson, Paul Gerrard

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Chapter 3. Linear Models

This chapter will cover linear models, which are probably the most commonly used statistical methods to study the relationships between variables. The generalized linear model section will delve into a bit more detail than typical R books, discussing the nature of link functions and canonical link functions:

  • Linear regression
  • Linear model fits
  • Analysis of variance models
  • Generalized linear models
  • Link functions and canonical link functions
  • Generalized additive models
  • Principal components analysis
  • Clustering
  • Discriminant analysis

An overview of statistical modeling

In order to explore the relationship between data and a set of experimental conditions, we often rely on statistical modeling. One of the central purposes of R is to estimate ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required