# predict.densityMclust: Density estimate of multivariate observations by Gaussian... In mclust: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

## Description

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

## Usage

 ```1 2``` ``` ## S3 method for class 'densityMclust' predict(object, newdata, what = c("dens", "cdens"), logarithm = FALSE, ...) ```

## Arguments

 `object` an object of class `'densityMclust'` resulting from a call to `densityMclust`. `newdata` 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`. `what` 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). `logarithm` 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(s)

Luca Scrucca

`Mclust`.

## Examples

 ```1 2 3 4 5 6 7 8 9``` ```## Not run: x <- faithful\$waiting dens <- densityMclust(x) x0 <- seq(50, 100, by = 10) d0 <- predict(dens, x0) plot(dens) points(x0, d0, pch = 20) ## End(Not run) ```

### Example output

```Package 'mclust' version 5.3
Type 'citation("mclust")' for citing this R package in publications.
```

mclust documentation built on July 2, 2018, 9:03 a.m.