vgam-class
object can be plotted
with plotvgam()
. These are on the scale of the linear/additive
predictor.plotvgam(x, newdata = NULL, y = NULL, residuals = NULL,
rugplot = TRUE, se = FALSE, scale = 0, raw = TRUE,
offset.arg = 0, deriv.arg = 0, overlay = FALSE,
type.residuals = c("deviance","working","pearson","response"),
plot.arg = TRUE, which.term = NULL, which.cf = NULL,
control = plotvgam.control(...), varxij = 1, ...)
vgam()
, vglm()
, or rrvglm()
.TRUE
then residuals are plotted.
See type.residuals
TRUE
then a rug plot is plotted at the
foot of each plot. These values are jittered to expose ties.TRUE
then approximate $\pm 2$ pointwise
standard error bands are included in the plot.scale
wide.TRUE
then the smooth functions are those
obtained directly by the algorithm, and are plotted without
having to premultiply with the constraint matrices.
If FALSE
then the smooth functions have been premultoverlay
is TRUE
.
If overlay
is TRUE
and there is one covariate then
s()
terms,
it plots the derivative.TRUE
then component functions of the same
covariate are overlaid on each other.
The functions are centered, so offset.arg
can be useful
when overlay
is TRUE
.residuals
is TRUE
then the first
possible value
of this vector, is used to specify the type of
residual.FALSE
then no plot is produced.which.term=c("s(age)", "s(height"))
or
which.term=c(2,5,9)
.
By default, all are plotted.plotvgam.control
.plotvgam.control
. This includes line colors,
line widths, line types, etc.xij
of vglm.control
was used,
this chooses which inner argument the component is plotted against.
This argument is related to raw=TRUE
anpreplot
slot of the object
assigned information regarding the plot.
Many of plotvgam()
's options can be found in
plotvgam.control
, e.g., line types, line widths,
colors.
Documentation accompanying the
vgam
,
plotvgam.control
,
predict.vgam
,
vglm
.coalminers = transform(coalminers, Age = (age - 42) / 5)
fit = vgam(cbind(nBnW,nBW,BnW,BW) ~ s(Age), binom2.or(zero=NULL), coalminers)
par(mfrow=c(1,3))
plot(fit, se=TRUE, ylim=c(-3,2), las=1)
plot(fit, se=TRUE, which.cf=1:2, lcol="blue", scol="red", ylim=c(-3,2))
plot(fit, se=TRUE, which.cf=1:2, lcol="blue", scol="red", overlay=TRUE)
Run the code above in your browser using DataLab