
Plots the fitted probabilities for some very simplified special cases of categorical data analysis models.
prplot(object, control = prplot.control(...), ...)prplot.control(xlab = NULL, ylab = "Probability", main = NULL, xlim = NULL,
ylim = NULL, lty = par()$lty, col = par()$col, rcol = par()$col,
lwd = par()$lwd, rlwd = par()$lwd, las = par()$las, rug.arg = FALSE, ...)
Currently only an cumulative
object.
This includes a propodds
object since that
VGAM family function is a special case of cumulative
.
List containing some basic graphical parameters.
See par
and ...
below.
See par
and ...
below.
Arguments starting with r
refer to the rug.
Argument rug.arg
is logical: add a rug for the distinct values of the
explanatory variable?
Arguments such as xlab
which are fed into prplot.control()
.
Only a small selection of graphical arguments from
par
are offered.
The object is returned invisibly with the preplot
slot assigned.
This is obtained by a call to plotvgam()
.
For models involving one term in the RHS of the formula this function plots the fitted probabilities against the single explanatory variable.
# NOT RUN {
pneumo <- transform(pneumo, let = log(exposure.time))
fit <- vglm(cbind(normal, mild, severe) ~ let, propodds, data = pneumo)
M <- npred(fit) # Or fit@misc$M
# }
# NOT RUN {
prplot(fit)
prplot(fit, lty = 1:M, col = (1:M)+2, rug = TRUE, las = 1,
ylim = c(0, 1), rlwd = 2)
# }
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