MixGHD-class: Class MixGHD.

In MixGHD: Model Based Clustering, Classification and Discriminant Analysis Using the Mixture of Generalized Hyperbolic Distributions

Class MixGHD.

Description

This class pertains to results of the application of function MGHD,MCGHD,MSGHD,cMSGHD.

Details

Plot the loglikhelyhood vale for each iteration of the EM algorithm. If p=2 it shows a contour plot. If 2<p<10 shows a splom of the data colored according to the cluster membership.

Slots

Index

Bayesian information criterion value for each combination of G and q.

BIC

Bayesian information criterion value.

gpar

A list of the model parameters.

loglik

The log-likelihood values.

map

A vector of integers indicating the maximum a posteriori classifications for the best model.

z

A matrix giving the raw values upon which map is based.

method

A string indicating the used method: MGHD, MGHFA, MSGHD, cMSGHD, MCGHD.

data

A matrix or data frame such that rows correspond to observations and columns correspond to variables.

par

(only for MCGHD)A list of the model parameters in the rotated space.

Methods

signature(x = "MixGHD", y = "missing")

S4 method for plotting objects of MixGHD-class.

Author(s)

Cristina Tortora, Aisha ElSherbiny, Ryan P. Browne, Brian C. Franczak, and Paul D. McNicholas. Maintainer: Cristina Tortora <[e-mail]>

See Also

MixGHD-class,MGHD,MCGHD,MSGHD,cMSGHD,MGHFA

Examples

##loading banknote data
data(bankruptcy)


##model estimation
model=MSGHD(bankruptcy[,2:3],G=2,max.iter=30)

#result
summary(model)
plot(model)

MixGHD documentation built on May 11, 2022, 5:12 p.m.