Description Usage Arguments Details Value References See Also Examples
Computes different sets of initial values for finite mixtures of unrestricted multivariate skew t (FM-uMST) model based on an initial clustering.
1 | fmmst.init(g, dat, known=NULL, clust=NULL, nkmeans=20, tmethod=1)
|
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 |
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 |
tmethod |
(optional) an integer indicating which method to use when computing t distribution function values.
See |
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), fmmst.init()
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 dfmmst
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 of initializations for fmmst
, each 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, McLachlan G (2011). On the fitting of mixtures of multivariate skew t-distributions via the EM algorithm. arXiv:1109.4706 [stat.ME]
Lee, S. and McLachlan, G.J. (2014) Finite mixtures of multivariate skew t-distributions: some recent and new results. Statistics and Computing, 24, 181-202.
Lee, S. and McLachlan, G.J. (2013) EMMIXuskew: An R
package for
fitting mixtures of multivariate skew t-distributions via the EM algorithm.
Journal of Statistical Software, 55(12), 1-22.
URL http://www.jstatsoft.org/v55/i12/.
rfmmst
, dfmmst
, fmmst.contour.2d
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | #a short demo using AIS data
data(ais)
Fit.init <- fmmst.init(2, ais[,c(2,12)])
#the number of available initializations
length(Fit.init)
#getting the first set of available initialization
Fit.init[[1]]
## Not run:
Fit1 <- fmmst(2, ais[,c(2,12)], initial=Fit.init[[1]])
Fit2 <- fmmst(2, ais[,c(2,12)], initial=Fit.init[[2]])
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.