expectation-maximization algorithm.
em.RdLearn parameters of a network using the Expectation-Maximization algorithm.
Usage
em(x, dataset, threshold = 0.001, max.em.iterations = 10, ess = 1)
# S4 method for 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").