fmx_cluster {QuantileGH}R Documentation

Naive Estimates of Finite Mixture Distribution via Clustering

Description

Naive estimates for finite mixture distribution fmx via clustering.

Usage

fmx_cluster(
  x,
  K,
  distname = c("GH", "norm", "sn"),
  constraint = character(),
  ...
)

Arguments

x

numeric vector, observations

K

integer scalar, number of mixture components

distname

character scalar, name of parametric distribution of the mixture components

constraint

character vector, parameters (g and/or h for Tukey g-&-h mixture) to be set at 0. See function fmx_constraint for details.

...

additional parameters, currently not in use

Details

First of all, if the specified number of components K\geq 2, trimmed k-means clustering with re-assignment will be performed; otherwise, all observations will be considered as one single cluster. The standard k-means clustering is not used since the heavy tails of Tukey g-&-h distribution could be mistakenly classified as individual cluster(s).

In each of the one or more clusters,

Value

Function fmx_cluster returns an fmx object.


[Package QuantileGH version 0.1.7 Index]