R: Probability Plots for Categorical Data Analysis

prplot {VGAM} | R Documentation

## 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, ...)

### 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.

### Value

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

### Note

This function is rudimentary.

### See Also

`cumulative`.

### Examples

    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)

[Package VGAM version 1.0-3 Index]