print.discdd.misclass: Printing results of discriminant analysis of discrete probability distributions

Description

Applies to an object of class "discdd.misclass". Prints the numerical results of discdd.misclass.

Usage

# S3 method for discdd.misclass
print(x, dist.print=FALSE, prox.print=FALSE, digits=2, ...)

Arguments

x: object of class "discdd.misclass", returned by discdd.misclass.
dist.print: logical. Its default value is FALSE. If TRUE, prints the matrix of distances between, on one side, the groups (densities) and, on the other side, the classes (of groups or densities).
prox.print: logical. Its default value is FALSE. If TRUE, prints the matrix of proximity indices (in percent) )between, on one side, the groups (densities) and, on the other side, the classes (of groups or densities).
digits: numeric. Number of significant digits for the display of numerical results.
...: optional arguments to print methods.

Author

Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Gilles Hunault, Sabine Demotes-Mainard

Details

By default, are printed the whole misallocation ratio, the confusion matrix (allocations versus origins) with the misallocation ratios per class, and the data frame whose rows are the groups, and whose columns are the origin classes and allocation classes, and a logical variable indicating misclassification.

If dist.print = TRUE or prox.print = TRUE, the distances or proximity indices (in percent) between groups and classes, are displayed.

Examples

Run this code

data("castles.dated")
stones <- castles.dated$stones
periods <- castles.dated$periods
stones$height <- cut(stones$height, breaks = c(19, 27, 40, 71), include.lowest = TRUE)
stones$width <- cut(stones$width, breaks = c(24, 45, 62, 144), include.lowest = TRUE)
stones$edging <- cut(stones$edging, breaks = c(0, 3, 4, 8), include.lowest = TRUE)
stones$boss <- cut(stones$boss, breaks = c(0, 6, 9, 20), include.lowest = TRUE )

castlefh <- folderh(periods, "castle", stones)

res <- discdd.misclass(castlefh, "period")

print(res)