visreg is an R package for displaying the results of a fitted model in terms of how a predictor variable x
affects an outcome y
. The implementation of visreg takes advantage of object-oriented programming in R, meaning that it works with virtually any type of formula-based model in R provided that the model class provides a predict()
method: lm
, glm
, gam
, rlm
, nlme
, lmer
, coxph
, svm
, randomForest
and many more.
To install the latest release version from CRAN:
install.packages("visreg")
To install the latest development version from GitHub:
remotes::install_github("pbreheny/visreg")
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, which uses the gam()
function from mgcv:
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 more information 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.
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