plotGAM: GAM plotting using ggplot2

In neuroconductor/voxel: Mass-Univariate Voxelwise Analysis of Medical Imaging Data

Description

GAM plotting using ggplot2

Usage

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)
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)

neuroconductor/voxel documentation built on May 20, 2021, 9:39 p.m.