em: expectation-maximization algorithm.

Description Usage Arguments Value Examples

Description

Learn parameters of a network using the Expectation-Maximization algorithm.

Usage

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em(x, dataset, threshold = 0.001, max.em.iterations = 10, ess = 1)

## S4 method for signature 'InferenceEngine,BNDataset'
em(x, dataset, threshold = 0.001, max.em.iterations = 10, ess = 1)

Arguments

x

an InferenceEngine.

dataset

observed dataset with missing values for the Bayesian Network of x.

threshold

threshold for convergence, used as stopping criterion.

max.em.iterations

maximum number of iterations to run in case of no convergence.

ess

Equivalent Sample Size value.

Value

a list containing: an InferenceEngine with a new updated network ("InferenceEngine"), and the imputed dataset ("BNDataset").

Examples

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## Not run: 
em(x, dataset)

## End(Not run)

bnstruct documentation built on July 2, 2020, 2:26 a.m.