R: Density estimate of multivariate observations by Gaussian...

predict.densityMclust {mclust} | R Documentation

## Density estimate of multivariate observations by Gaussian finite mixture modeling

### Description

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

### Usage

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

### 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).
`...` | 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

### 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

    x = faithful$waiting
    dens = densityMclust(x)
    x0 = seq(50, 100, by = 10)
    d0 = predict(dens, x0)
    plot(dens)
    points(x0, d0, pch = 20)

[Package mclust version 5.3 Index]