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.

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]