mclust (version 5.3)

summary.Mclust: Summarizing Gaussian Finite Mixture Model Fits

Description

Summary method for class "Mclust".

Usage

# S3 method for Mclust
summary(object, parameters = FALSE, classification = FALSE, …)
# S3 method for summary.Mclust
print(x, digits = getOption("digits"), …)

Arguments

object

An object of class 'Mclust' resulting of a call to Mclust or densityMclust.

x

An object of class 'summary.Mclust', usually, a result of a call to summary.Mclust.

parameters

Logical; if TRUE, the parameters of mixture components are printed.

classification

Logical; if TRUE, the MAP classification/clustering of observations is printed.

digits

The number of significant digits to use when printing.

…

Further arguments passed to or from other methods.

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, densityMclust.

Examples

# NOT RUN {
mod1 = Mclust(iris[,1:4])
summary(mod1)
summary(mod1, parameters = TRUE, classification = TRUE)

mod2 = Mclust(iris[,1:4], G = 1)
summary(mod2, parameters = TRUE, classification = TRUE)

mod3 = Mclust(iris[,1:4], prior = priorControl())
summary(mod3)

mod4 = Mclust(iris[,1:4], prior = priorControl(functionName="defaultPrior", shrinkage=0.1))
summary(mod4, parameters = TRUE, classification = TRUE)
# }