mclust (version 3.4.7)

mclustDAtest: MclustDA Testing

Description

Testing phase for MclustDA discriminant analysis.

Usage

mclustDAtest(data, models)

Arguments

data

A numeric vector, matrix, or data frame of observations to be classified.

models

A list of MCLUST-style models including parameters, usually the result of applying mclustDAtrain to some training data.

Value

• A matrix in which the [i,j]th entry is the density for that test observation i in the model for class j.

References

C. Fraley and A. E. Raftery (2002). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631.

C. Fraley and A. E. Raftery (2006). MCLUST Version 3 for R: Normal Mixture Modeling and Model-Based Clustering, Technical Report no. 504, Department of Statistics, University of Washington.

Details

Apply summary to the output to obtain the classification of the test data.

See Also

summary.mclustDAtest, classError, mclustDAtrain

Examples

odd <- seq(1, nrow(cross), by = 2)
train <- mclustDAtrain(cross[odd,-1], labels = cross[odd,1]) ## training step
summary(train)

even <- odd + 1
test <- mclustDAtest(cross[even,-1], train) ## compute model densities
clEven <- summary(test)$class ## classify training set
classError(clEven,cross[even,1])