initial.RndEM.worker: Initialization of RndEM for X.worker
Description
This function implements RndEM procedure for model-based clustering
based on X.worker.
Usage
initial.RndEM.worker(PARAM)
Arguments
PARAM
an original set of parameters generated
by set.global.
Value
The best initial starting points will be returned among all random
starting points. The number of random starting points is assigned by
set.global to a list variable CONTROL.
See the help page
of initial.em.worker and set.global
for details.
Details
The RndEM procedure is implemented by randomly picking
CONTROL$RndEM.iter starting points from data X.worker
and run one E-step to obtain the log likelihood.
Then pick the starting point with the highest log likelihood as the
best choice to pursue the MLEs in further EM iterations.
This function repeatedly run initial.em.worker by
CONTROL$RndEM.iter random starts and pick the best initializations
from the random starts.
References
High Performance Statistical Computing Website:
http://thirteen-01.stat.iastate.edu/snoweye/hpsc/
Maitra, R. (2009)
Initializing partition-optimization algorithms,
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
6:1, 114-157.