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(...), ...)vgam(), vglm(), or rrvglm().TRUE, residuals are plotted. See
type.residualsTRUE, a rug plot is plotted at the
foot of each plot. These values are jittered to expose ties.TRUE, approximate $\pm 2$ pointwise
standard error bands are included in the plot.scale wide.TRUE, the smooth functions are those
obtained directly by the algorithm, and are
plotted without
having to premultiply with the constraint matrices.
If FALSE, the smooth functions have been premultoverlay is TRUE.
If overlay is TRUE and there is one covariate, using s() terms,
it plots the derivative.TRUE, 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, the first
possible value
of this vector, is used to specify the type of
residual.FALSE, 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.preplot slot of the object
assigned information regarding the plot.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.data(coalminers)
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