em {bnstruct} | R Documentation |
expectation-maximization algorithm.
Description
Learn 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 signature 'InferenceEngine,BNDataset'
em(x, dataset, threshold = 0.001, max.em.iterations = 10, ess = 1)
Arguments
x |
an |
dataset |
observed dataset with missing values for the Bayesian Network of |
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
## Not run:
em(x, dataset)
## End(Not run)
[Package bnstruct version 1.0.15 Index]