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em (version 1.0.0)

Generic EM Algorithm

Description

A generic function for running the Expectation-Maximization (EM) algorithm within a maximum likelihood framework, based on Dempster, Laird, and Rubin (1977) is implemented. It can be applied after a model fitting using R's existing functions and packages.

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Install

install.packages('em')

Monthly Downloads

45

Version

1.0.0

License

GPL (>= 3)

Issues

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Repository

https://github.com/wudongjie/em

Maintainer

Dongjie Wu

Last Published

January 11th, 2023

Functions in em (1.0.0)

fit.den.multinom

Fit the density function for a multinomial regression model.

fit.den.glmerMod

Fit the density function for a generalized linear mixed effect model.

Fit the density function for a linear regression model.

Fit the density function for a generalized non-linear regression model.

fit.den.fitdist

Fitting the density function using in `fitdistrplus::fitdist()`

Multiple run of EM algorithm

mstep.concomitant.refit

The refit of for the concomitant model. This section was inspired by Flexmix.

print.summary.em

Print the `summary.em` object

K-mean initialization

model-based agglomerative hierarchical clustering

Simulated Data from a logistic regression

Fit the density function for a generalized linear regression model.

Predict the fitted finite mixture models

M-Step of EM algorithm

mstep.concomitant

The mstep for the concomitant model.

Random initialization

Fit the density function for a `nnet` model.

init.em.random.weights

Random initialization with weights

Fit the density function for a panel regression model.

S-step of EM algorithm

Print the `em` object

init.em.sample5

Initialization using sampling 5 times.

Simulated Regression Data

Plot the fitted results of EM algorithm

Simulated Data from a conditional logistic regression

Summaries of fitted finite mixture models using EM algorithm

multi.em.default

Default generic for multi.em

This function computes logLik of EM Algorithm.

Transform a factor variable to a matrix of dummy variables

Fit the density function for a fitted model.

The em function for glmerMod

This function performs an E-Step of EM Algorithm.

Fit the density for the survival::clogit

C-Step of EM algorithm

The default em function

The em function for `panelmodel` such as `plm`.

The em function for `survival::clogit`.

The default em function

A Generic EM Algorithm

Initialization of EM algorithm

Flatten a data.frame or matrix by column or row with its name. The name will be transformed into the number of row/column plus the name of column/row separated by `.`.