splitEM_GLM: Split-small EM scheme.

In multinomialLogitMix: Clustering Multinomial Count Data under the Presence of Covariates

Split-small EM scheme.

Description

Split two randomly selected clusters based on a model with one component smaller than the current one. This procedure is repeated within a small-EM scheme. The best split is chose to initialize the model.

Usage

splitEM_GLM(y, x, K, smallerModel, tsplit = 10, maxIter = 20, 
	emthreshold = 1e-08, maxNR = 5, nCores, 
	split = TRUE, R0, method)

Arguments

y	y
x	x
K	k
smallerModel	smla
tsplit	tsp
maxIter	max
emthreshold	thr
maxNR	maxn
nCores	nc
split	spi
R0	ro
method	meth

Value

val

Author(s)

Panagiotis Papastamoulis

References

Papastamoulis, P., Martin-Magniette, M. L., and Maugis-Rabusseau, C. (2016). On the estimation of mixtures of Poisson regression models with large number of components. Computational Statistics & Data Analysis, 93, 97-106.

multinomialLogitMix documentation built on July 26, 2023, 6:07 p.m.