Visualization of Regression Models

visreg provides a number of plotting functions for visualizing fitted regression models: regression functions, confidence bands, partial residuals, interactions, and more. visreg is compatible with virtually all formula-based models in R that provide a predict method: lm, glm, gam, rlm, nlme, lmer, coxph, svm, randomForest and many more.

The basic usage is that you fit a model, for example:

fit <- lm(Ozone ~ Solar.R + Wind + Temp, data=airquality)

and then you pass it to visreg:

visreg(fit, "Wind")

A more complex example, using the mgcv package:

airquality$Heat <- cut(airquality$Temp, 3, labels=c("Cool", "Mild", "Hot"))
fit <- gam(Ozone ~ s(Wind, by=Heat, sp=0.1), data=airquality)
visreg(fit, "Wind", "Heat", gg=TRUE, ylab="Ozone")

For details on visreg syntax and how to use it, see:

• The online documentation at http://pbreheny.github.io/visreg contains many examples of visreg plots and the code to create them.
• Breheny P and Burchett W. (2013). Visualizing regression models using visreg.

The website focuses more on syntax, options, and user interface, while the paper goes into more depth regarding the statistical details.

If you have a question or feature request, please submit an issue.

To install:

• the latest released version: install.packages("visreg")
• the latest version (requires devtools): install_github("pbreheny/visreg")