Description Usage Arguments Details Value References See Also Examples
Computes different sets of initial values for finite mixtures of canonical fundamental skew t (FM-CFUST) model based on an initial clustering, transformation approiach, moment-based approach, or nested-model appraoch.
1 2 3 4 |
g |
a scalar specifying the number of components in the mixture model |
dat |
the data matrix giving the coordinates of the point(s) where the density is evaluated.
This is either a vector of length |
q |
a scalar specifying how many number of columns the skewness matrix |
initial |
(optional) a list containing the initial parameters of the mixture model.
See the 'Details' section. The default is |
known |
(optional) a list containing parameters of the mixture model that are known
and not required to be estimated. See the 'Details' section. The default is |
clust |
(optional) a numeric value of length |
nkmeans |
(optional) a numeric value indicating how many k-means trials to be used
when searching for initial values. The default is |
method |
(optional) a string indicating which method to use to generate initial values. See Details. |
As the EM algorithm is sensitive to the starting value,
it is highly recommended to apply a wide range different initializations.
To obtain different sets of starting values using the strategy described in
Section 5.1.3 of Lee and McLachlan (2014), init.cfust()
can be used,
which will return a list of objects with the same structure as initial
.
An example is given in the examples section below.
The argument known
, if specified, is a list structure containing
at least one of mu
, sigma
, delta
, dof
, pro
(See dfmcfust
for the structure of each of these elements).
Note that although not all parameters need to be provided in known
,
the parameters that are provided must be fully specified.
They cannot be partially specified, e.g. only some elements or some components are specified.
a list object containing the following parameters:
mu |
a list of |
sigma |
a list of |
delta |
a list of |
dof |
a numeric vector of length |
pro |
a vector of length of |
tau |
an |
clusters |
a vector of length n of initial partition. |
loglik |
the initial log likelihood value. |
Lee S.X. and McLachlan, G.J. (2016). Finite mixtures of canonical fundamental skew t-distributions: the unification of the restricted and unrestricted skew t-mixture models. Statistics and Computing 26, 573-589.
Lee S.X. and McLachlan, G.J. (2017). EMMIXcskew: An R Package for the Fitting of a Mixture of Canonical Fundamental Skew t-Distributions. Journal of Statistical Software 83(3), 1-32. URL 10.18637/jss.v083.i03.
rfmcfust
, dfmcfust
, fmcfust.contour.2d
1 2 3 4 5 | #a short demo using geyser data
library(MASS)
data(geyser)
initial.transformation <- init.cfust(3, geyser, method="transformation")
initial.transformation$loglik
|
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