Component functions of a 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, ...)
Data frame. May be used to reconstruct the original data set.
Unused.
Logical. If TRUE
then residuals are plotted.
See type.residuals
Logical. If TRUE
then a rug plot is plotted at the
foot of each plot. These values are jittered to expose ties.
Logical. If TRUE
then approximate \(\pm 2\) pointwise
standard error bands are included in the plot.
Numerical. By default, each plot will have its own
y-axis scale. However, by specifying a value, each plot's y-axis
scale will be at least scale
wide.
Logical. If 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 premultiply by
the constraint matrices.
The raw
argument is directly fed into predict.vgam()
.
Numerical vector of length \(r\).
These are added to the component functions. Useful for
separating out the functions when overlay
is TRUE
.
If overlay
is TRUE
and there is one covariate then
using the intercept values as the offsets can be a good idea.
Numerical. The order of the derivative.
Should be assigned an small
integer such as 0, 1, 2. Only applying to s()
terms,
it plots the derivative.
Logical. If 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
.
if residuals
is TRUE
then the first
possible value
of this vector, is used to specify the type of residual.
Logical. If FALSE
then no plot is produced.
Character or integer vector containing all terms to be
plotted, e.g., which.term = c("s(age)", "s(height"))
or
which.term = c(2, 5, 9)
.
By default, all are plotted.
An integer-valued vector specifying which linear/additive predictors are to be plotted. The values must be from the set {1,2,…,\(r\)}. By default, all are plotted.
Other control parameters. See plotvgam.control
.
Other arguments that can be fed into
plotvgam.control
. This includes line colors,
line widths, line types, etc.
Positive integer.
Used if xij
of vglm.control
was used,
this chooses which inner argument the component is plotted against.
This argument is related to raw = TRUE
and terms such as
NS(dum1, dum2)
and constraint matrices that have more than
one column. The default would plot the smooth against dum1
but setting varxij = 2
could mean plotting the smooth against
dum2
.
See the VGAM website for further information.
The original object, but with the preplot
slot of the object
assigned information regarding the plot.
In this help file \(M\) is the number of linear/additive predictors, and \(r\) is the number of columns of the constraint matrix of interest.
Many of plotvgam()
's options can be found in
plotvgam.control
, e.g., line types, line widths,
colors.
vgam
,
plotvgam.control
,
predict.vgam
,
plotvglm
,
vglm
.
# NOT RUN {
coalminers <- transform(coalminers, Age = (age - 42) / 5)
fit <- vgam(cbind(nBnW, nBW, BnW, BW) ~ s(Age),
binom2.or(zero = NULL), data = coalminers)
# }
# NOT RUN {
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 = "orange",
ylim = c(-3, 2))
plot(fit, se = TRUE, which.cf = 1:2, lcol = "blue", scol = "orange",
overlay = TRUE)
# }
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