.em.method {phyclust} | R Documentation |
EM Methods and Algorithms
Description
The varied EM algorithms are implemented in C. The first element is the default value. This is a read-only object and the elemental order is followed in C.
Usage
.em.method
Format
A character vector contains implemented EM algorithms in C.
Details
EM
(default) stands for the standard EM algorithm, ECM
stands for Expectation/Conditional Maximization algorithm, and AECM
stands for Alternating ECM algorithm.
The performance is roughly about AECM
> EM
~ ECM
which
are dependent on the separations of data set.
Author(s)
Wei-Chen Chen wccsnow@gmail.com
References
Phylogenetic Clustering Website: https://snoweye.github.io/phyclust/
Dempster, A. and Laird, N. and Rubin, D. (1977) “Maximum Likelihood Estimation from Incomplete Data via the EM Algorithm”, Journal of the Royal Statistical Society Series B, 39:3, 1-38.
Meng, X.-L. and Rubin, D. (1993) “Maximum likelihood estimation via the ECM algorithm: A general framework”, Biometrika, 80:2, 511-567.
Meng, X.-L. and van Dyk, D. (1997) “The EM Algorithm — an Old Folk-song Sung to a Fast New Tune (with discussion)”, Journal of the Royal Statistical Society Series B, 59, 511-567.
See Also
.show.option
,
.EMC
,
.EMControl
,
phyclust
.
Examples
## Not run:
library(phyclust, quiet = TRUE)
.em.method
## End(Not run)