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 |
|
K |
integer scalar, number of mixture components |
distname |
character scalar, name of parametric distribution of the mixture components |
constraint |
character vector,
parameters ( |
... |
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,
letterValue-based estimates of Tukey
g
-&-h
distribution (Hoaglin, 2006) are calculated, for anyK\geq 1
, serving as the starting values for QLMD algorithm. These estimates are provided by function fmx_cluster.the median and mad will serve as the starting values for
\mu
and\sigma
(orA
andB
for Tukeyg
-&-h
distribution, withg = h = 0
), for QLMD algorithm whenK = 1
.
Value
Function fmx_cluster returns an fmx object.