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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 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.

Installation

To install the latest release version from CRAN:

install.packages("visreg")

To install the latest development version from GitHub:

remotes::install_github("pbreheny/visreg")

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Version

Install

install.packages('visreg')

Monthly Downloads

5,463

Version

2.7.0

License

GPL-3

Maintainer

Last Published

June 4th, 2020

Functions in visreg (2.7.0)

visreg

Visualization of regression functions
plot.visreg

Visualization of regression functions
plot.visreg2d

Visualization of regression functions for two variables
visreg2d

Visualization of regression functions for two variables
subset.visreg

Subset a visreg object
visregList

Join multiple visreg objects together in a list
visreg-faq

Frequently Asked Questions for visreg
visreg-package

Visualization of regression models