mclust (version 5.2.2)

predict.MclustDA: Classify multivariate observations by Gaussian finite mixture modeling

Description

Classify multivariate observations based on Gaussian finite mixture models estimated by MclustDA.

Usage

"predict"(object, newdata, prior, ...)

Arguments

object

an object of class 'MclustDA' resulting from a call to MclustDA.

newdata

a data frame or matrix giving the data. If missing the train data obtained from the call to MclustDA are classified.

prior

the prior probabilities of the classes; by default, this is set at the proportions in the training data.

...

further arguments passed to or from other methods.

Value

Returns a list of with the following components:

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, A. E. Raftery, T. B. Murphy and L. Scrucca (2012). mclust Version 4 for R: Normal Mixture Modeling for Model-Based Clustering, Classification, and Density Estimation. Technical Report No. 597, Department of Statistics, University of Washington.

See Also

MclustDA.

Examples

## Not run: 
# odd <- seq(from = 1, to = nrow(iris), by = 2)
# even <- odd + 1
# X.train <- iris[odd,-5]
# Class.train <- iris[odd,5]
# X.test <- iris[even,-5]
# Class.test <- iris[even,5]
# 
# irisMclustDA <- MclustDA(X.train, Class.train)
# 
# predTrain <- predict(irisMclustDA)
# predTrain
# predTest <- predict(irisMclustDA, X.test)
# predTest
# ## End(Not run)