One EM step only for model-based clustering of finite mixture Gaussian
models with unstructured dispersions.
This is a core function of em.step.
em.onestep.dmat is a ddmatrix version of em.onestep.
Usage
em.onestep(PARAM)
em.onestep.dmat(PARAM)
Arguments
PARAM
an original set of parameters generated
by set.global.
Value
This function is one EM step. The global variables will be updated and
a new PARAM will be returned.
See the help page of PARAM or PARAM.org
for details.
Details
A global variable called X.spmd should exist in the
.pmclustEnv
environment, usually the working environment. The X.spmd
is the data matrix to be clustered, and this matrix has a dimension
N.spmd by p.
The PARAM will be a local variable for the current iteration inside
em.onestep,
and this variable is a list containing all parameters related to models.
This function also updates in the parameters by the EM algorithm, and
return a new PARAM for the next iteration.
The details of list elements are initially
generated by set.global.
References
High Performance Statistical Computing (HPSC) Website:
http://thirteen-01.stat.iastate.edu/snoweye/hpsc/
Programming with Big Data in R Website:
http://r-pbd.org/