GAM plotting using ggplot2

Source: R/plotGAM.R

GAM plotting using ggplot2

plotGAM(gamFit, smooth.cov, groupCovs = NULL, orderedAsFactor = T,
  rawOrFitted = F, plotCI = T)

Arguments

gamFit

fitted gam model as produced by mgcv::gam()
smooth.cov

(character) name of smooth term to be plotted
groupCovs

(character) name of group variable to plot by, if NULL (default) then there are no groups in plot
orderedAsFactor

if TRUE then the model is refitted with ordered variables as factors.
rawOrFitted

If FALSE (default) then only smooth terms are plotted; if rawOrFitted = "raw" then raw values are plotted against smooth; if rawOrFitted = "fitted" then fitted values are plotted against smooth
plotCI

if TRUE (default) upper and lower confidence intervals are added at 2 standard errors above and below the mean

Value

Returns a ggplot object that can be visualized using the print() function

See also

Other Plotting: plotGAMM

Examples


data <- data.frame(x = rep(1:20, 2), group = rep(1:2, each = 20))
set.seed(1)
data$y <- (data$x^2)*data$group*3 + rnorm(40, sd = 200)
data$group <- ordered(data$group)

gam <- mgcv::gam(y ~ s(x) + group, data=data)

plot1 <- plotGAM(gamFit = gam, smooth.cov = "x", groupCovs = NULL,
                  rawOrFitted = "raw", plotCI=TRUE, orderedAsFactor = FALSE)
#> Warning: There are one or more factors in the model fit, please consider plotting by group since plot might be unprecise
gam <- mgcv::gam(y ~ s(x) + group + s(x, by=group), data=data)
plot2 <- plotGAM(gamFit = gam, smooth.cov = "x", groupCovs = "group",
                             rawOrFitted = "raw", orderedAsFactor = FALSE)