Compute density estimation for multivariate observations based on Gaussian finite mixture models estimated by densityMclust.

# S3 method for densityMclust
predict(object, newdata, what = c("dens", "cdens", "z"), logarithm = FALSE, ...)

## Arguments

object an object of class 'densityMclust' resulting from a call to densityMclust. a vector, a data frame or matrix giving the data. If missing the density is computed for the input data obtained from the call to densityMclust. a character string specifying what to retrieve: "dens" returns a vector of values for the mixture density; "cdens" returns a matrix of component densities for each mixture component (along the columns); "z" returns a matrix of conditional probabilities of each data point to belong to a mixture component. A logical value indicating whether or not the logarithm of the density or component densities should be returned. further arguments passed to or from other methods.

## Value

Returns a vector or a matrix of densities evaluated at newdata depending on the argument what (see above).

## Author

Luca Scrucca

Mclust.

## Examples

if (FALSE) {
x <- faithful\$waiting
dens <- densityMclust(x)
x0 <- seq(50, 100, by = 10)
d0 <- predict(dens, x0)
plot(dens)
points(x0, d0, pch = 20)
}