mclust (version 5.2.2)

predict.Mclust: Cluster multivariate observations by Gaussian finite mixture modeling

Description

Cluster prediction for multivariate observations based on Gaussian finite mixture models estimated by Mclust.

Usage

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

Arguments

object

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

newdata

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

...

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

Mclust.

Examples

model <- Mclust(faithful)

# predict cluster for the observed data
pred <- predict(model) 
str(pred)
pred$z              # equal to model$z
pred$classification # equal to 
plot(faithful, col = pred$classification, pch = pred$classification)

# predict cluster over a grid
grid <- apply(faithful, 2, function(x) seq(min(x), max(x), length = 50))
grid <- expand.grid(eruptions = grid[,1], waiting = grid[,2])
pred <- predict(model, grid)
plot(grid, col = mclust.options("classPlotColors")[pred$classification], pch = 15, cex = 0.5)
points(faithful, pch = model$classification)