In this chapter, we will cover the following recipes:
- Different types of regression
- Fitting a linear regression model with lm
- Summarizing linear model fits
- Using linear regression to predict unknown values
- Generating a diagnostic plot of a fitted model
- Fitting multiple regression
- Summarizing multiple regression
- Using multiple regression to predict the values
- Fitting a polynomial regression model with lm
- Fitting a robust linear regression model with rlm
- Studying a case of linear regression on SLID data
- Applying the Gaussian model for generalized linear regression
- Applying the Poisson model for generalized linear regression
- Applying the Binomial model for generalized linear regression
- Fitting a generalized additive model to data
- Visualizing a generalized additive model
- Diagnosing a generalized additive model
