This package facilitates daily modeling routines with GA(M)Ms by the
mgcv package (Wood, 2017). Suppose you already fitted a GAM below, using
mgcv::gam or mgcv::bam:
print(mdl)
#>
#> Family: gaussian
#> Link function: identity
#>
#> Formula:
#> y ~ s(x0) + s(x1) + s(x2) + ti(x0, x1) + ti(x0, x2) + ti(x1,
#> x2) + ti(x0, x1, x2)
#>
#> Estimated degrees of freedom:
#> 5.34 5.51 5.03 9.38 8.29 10.88 7.08
#> total = 52.51
#>
#> GCV score: 1.048869
Summed effects
Summed-effects can be visualized by mgcv::vis.gam, or
itsadug::fvisgam (van Rij, 2020). The same plot can also be plotted by
mgcv::plot_contour as below:
library(mgcv)
#> Loading required package: nlme
#> This is mgcv 1.9-4. For overview type '?mgcv'.
vis.gam(mdl, view=c('x1','x2'), plot.type='contour')
plot_contour(mdl, view=c('x1','x2'))
There is no correct way in choosing the number of contour lines and
their values. In gamutil::plot_contour, you can use user-defined contour
lines by the optional arguments “contour.line.breaks” and
“contour.color.breaks” for contour lines and contour colors
respectively:
lbr <- seq(-10, 10, by=1.0)
cbr <- seq(-10, 10, by=0.1)
plot_contour(mdl, view=c('x1','x2'),
contour.line.breaks=lbr, contour.color.breaks=cbr)
Partial effects
Partial effects can be visualized by mgcv::plot.gam or
itsadug::pvisgam. The same plot can be obtained with
gamutil::plot_contour as below:
lbr <- seq(-5, 5, by=0.50)
cbr <- seq(-5, 5, by=0.05)
plot_contour(mdl, view=c('x1','x2'), summed=FALSE, terms.size='min',
verbose=TRUE, contour.line.breaks=lbr, contour.color.breaks=cbr)
#> Selected:
#> ti(x1,x2)
The optional argument “terms.size=‘min’” ensures that you include
only the term that contains the variables specified in “view”, namely
“x1” and “x2” in this example.
Partially-summed effects
The argument “terms.size” can take three values. They are “min”,
“medium”, and “max”. “min” is intended to plot only one term, i.e.,
partial effects. “medium” includes all the terms that contain the
variables specified in “view” but no other variables. In the current
example, it would include “s(x1)”, “s(x2)”, and “ti(x1,x2)”. Note that
“ti(x0, x1)”, “ti(x0,x2)”, and ti(x0, x1, x2) are excluded, although
they contain one of the variables in “view”. They are excluded because
they also contain the variables that are not specified in “view”.
plot_contour(mdl, view=c('x1','x2'), summed=FALSE, terms.size='medium',
verbose=TRUE)
#> Selected:
#> s(x1)
#> s(x2)
#> ti(x1,x2)
In contrast, “terms.size=‘max’” plots all the terms that include at
least one of the variables specified in the “view” argument. In the
current example, it would include “s(x1)”, “s(x2)”, “ti(x0,x1)”,
“ti(x0,x2)”, “ti(x1,x2)”, and “ti(x0,x1,x2)”.
plot_contour(mdl, view=c('x1','x2'), summed=FALSE, terms.size='max',
verbose=TRUE)
#> Selected:
#> s(x1)
#> s(x2)
#> ti(x0,x1)
#> ti(x0,x2)
#> ti(x1,x2)
#> ti(x0,x1,x2)
Notes
The return value of gamutil::plot_contour is a ggplot object.
Therefore, you can modify the plot afterwards.
library(ggplot2)
plt <- plot_contour(mdl, view=c('x1','x2'), summed=FALSE, terms.size='medium',
verbose=TRUE)
#> Selected:
#> s(x1)
#> s(x2)
#> ti(x1,x2)
plt <- plt + theme(text=element_text(size=25))
plt
