mclust (version 2.1-14)

summary.mclustDAtrain: Models and classifications from mclustDAtrain

Description

The models selected in mclustDAtrain and the corresponding classfications.

Usage

summary.mclustDAtrain(object, ...)

Arguments

object

The output of mclustDAtrain.

...

Not used. For generic/method consistency.

Value

• A list identifying the model selected by mclustDAtrain for each class of training data and the corresponding classification.

References

C. Fraley and A. E. Raftery (2002a). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631. See http://www.stat.washington.edu/mclust. C. Fraley and A. E. Raftery (2002b). MCLUST:Software for model-based clustering, density estimation and discriminant analysis. Technical Report, Department of Statistics, University of Washington. See http://www.stat.washington.edu/mclust.

See Also

mclustDAtrain

Examples

set.seed(0)
n <- 100 ## create artificial data

x <- rbind(matrix(rnorm(n*2), n, 2) %*% diag(c(1,9)),
           matrix(rnorm(n*2), n, 2) %*% diag(c(1,9))[,2:1])
xclass <- c(rep(1,n),rep(2,n))
par(pty = "s")
mclust2Dplot(x, classification = xclass, type="classification", ask=FALSE)

odd <- seq(1, 2*n, 2)
train <- mclustDAtrain(x[odd, ], labels = xclass[odd]) ## training step
summary(train)