DEM (version 0.0.0.2)

The Distributed EM Algorithms in Multivariate Gaussian Mixture Models

Description

The distributed expectation maximization algorithms are used to solve parameters of multivariate Gaussian mixture models. The philosophy of the package is described in Guo, G. (2022) .

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Version

Install

install.packages('DEM')

Monthly Downloads

231

Version

0.0.0.2

License

MIT + file LICENSE

Maintainer

Qian Wang

Last Published

May 14th, 2022

Functions in DEM (0.0.0.2)

Skin

Skin segmentation

DMOEM

The DMOEM is an overrelaxation algorithm in distributed manner, which is used to solve the parameter estimation of multivariate Gaussian mixture model.

DEM1

The DEM1 algorithm is a divide and conquer algorithm, which is used to solve the parameter estimation of multivariate Gaussian mixture model.

DOEM2

The DOEM2 algorithm is an online EM algorithm in distributed manner, which is used to solve the parameter estimation of multivariate Gaussian mixture model.

DEM2

The DEM2 algorithm is a one-step average algorithm in distributed manner, which is used to solve the parameter estimation of multivariate Gaussian mixture model.

The EM algorithm is used to solve the parameter estimation of multivariate Gaussian mixture model.

DOEM1

The DOEM1 algorithm is an online EM algorithm in distributed manner, which is used to solve the parameter estimation of multivariate Gaussian mixture model.