plot.cv4postpr: Barplot of model misclassification
In AlexRego/edited_abc: Tools for Approximate Bayesian Computation (ABC)

Description Usage Arguments Details See Also Examples

Displays a barplot of either the proportion of simulations classified to any of the models or the mean misclassification probabilities of models for all tolerance levels in the "cv4postpr" object.

## S3 method for class 'cv4postpr'
plot(x, probs = FALSE, file = NULL, postscript
= FALSE, onefile = TRUE, ask = !is.null(deviceIsInteractive()), caption
= NULL, ...)

`x`	an object of class `"cv4postpr"`.
`probs`	logical, if `TRUE` the mean posterior model probabilities are plotted. If `FALSE` the frequencies of the simulations classified to the different models (default).
`file`	a character string giving the name of the file. See `postscript` for details on accepted file names. If `NULL` (the default) plots are printed to the null device (e.g. `X11`). If not `NULL` plots are printed on a `pdf` device. See also `postscript`.
`postscript`	logical; if `FALSE` (default) plots are printed on a `pdf` device, if `TRUE` on a `postscript` device.
`onefile`	logical, if `TRUE` (the default) allow multiple figures in one file. If `FALSE`, generate a file name containing the page number for each page. See `postscript` for further details.
`ask`	logical; if `TRUE` (the default), the user is asked before each plot, see `par(ask=.)`.
`caption`	captions to appear above the plot(s); `character` vector of valid graphics annotations, see `as.graphicsAnnot`. Can be set to `""` or `NA` to suppress all captions.
`...`	other parameters passed to `barplot`.

Model are distinguised with different intensities of the gray colour. The first model in alphabetic order has the darkest colour. If the classification of models is perfect (so that the frequency (or probability) of each model is zero for all but the correct model) each bar has a single colour of its corresponding model.

cv4postpr, summary.cv4postpr