plot.gcjc: Plot Method for Class 'gcjc'

In matsukik/grt: General Recognition Theory

Description

Plot the fitted data set and decision boundary.

Usage

## S3 method for class 'gcjc'
plot(x, fitdb = TRUE, initdb = FALSE, xlim = NULL, ylim = NULL, bg, pch, ...)

Arguments

x	object of class gcjc
fitdb	logical. If TRUE, the fitted decision bound is plotted. Default to TRUE
initdb	logical. If TRUE, the decision bound specified by the initial parameters is plotted. Default to FALSE
xlim	the x limits of the plot
ylim	the y limits of the plot
bg	the background color to be used for points. Default is c("white","gray")[response] where response represents the response vector of the model
pch	the symbols to be used as points. Default is c(21,24)[x$category]
...	further arguments.

Details

This function produces a scatter plot of data matrix in the x and (optionally) decision boundary specified within (i.e., x$par and/or x$initpar).

Examples

m <- list(c(100,200),c(100,100),c(200,100),c(200,200))
covs <- diag(30^2, ncol=2, nrow=2)
set.seed(1)
CJ <- grtrnorm(n=c(50,20,10,20), np=4, means=m, covs=covs)
CJ$category <- c(1,2,2,2)[CJ$category]
#create ramdom responses with 80% accuracy
CJ$response <- CJ$category
set.seed(1)
incorrect <- sample(1:100, size=20)
CJ$response[incorrect] <- abs(CJ$response[incorrect] - 3)

#now fit the model
m.cj <- gcjc(response ~ x1 + x2, data=CJ, config=2, category=CJ$category, zlimit=7)

plot(m.cj)

matsukik/grt documentation built on May 21, 2019, 12:57 p.m.