prplot: Probability Plots for Categorical Data Analysis

Description

Plots the fitted probabilities for some very simplified special cases of categorical data analysis models.

Usage

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, ...)

Value

The object is returned invisibly with the preplot slot assigned. This is obtained by a call to plotvgam().

Arguments

object: Currently only an cumulative object. This includes a propodds object since that VGAM family function is a special case of cumulative.
control: List containing some basic graphical parameters.
xlab, ylab, main, xlim, ylim, lty: See par and ... below.
col, rcol, lwd, rlwd, las, rug.arg: 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.

Details

For models involving one term in the RHS of the formula this function plots the fitted probabilities against the single explanatory variable.

Examples

Run this code

pneumo <- transform(pneumo, let = log(exposure.time))
fit <- vglm(cbind(normal, mild, severe) ~ let, propodds, data = pneumo)
M <- npred(fit)  # Or fit@misc$M
if (FALSE)  prplot(fit)
prplot(fit, lty = 1:M, col = (1:M)+2, rug = TRUE, las = 1,
       ylim = c(0, 1), rlwd = 2)