Probability Plots for Categorical Data Analysis
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, ...)object |
Currently only an |
control |
List containing some basic graphical parameters. |
xlab, ylab, main, xlim, ylim, lty |
See |
col, rcol, lwd, rlwd, las, rug.arg |
See |
... |
Arguments such as |
For models involving one term in the RHS of the formula this function plots the fitted probabilities against the single explanatory variable.
The object is returned invisibly with the preplot slot assigned.
This is obtained by a call to plotvgam().
This function is rudimentary.
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)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.