mmpc {bnlearn}R Documentation

Max-Min Parents and Children (MMPC) learning algorithm

Description

Estimate the underlying structure of a directed acyclic graph (DAG) from data using the Max-Min Parents and Children (MMPC) constraint-based algorithm.

Usage

  mmpc(x, cluster = NULL, whitelist = NULL, blacklist = NULL,
    test = NULL, alpha = 0.05, debug = FALSE, optimized = TRUE,
    strict = FALSE)

Arguments

x a data frame, containing the variables in the model.
cluster an optional cluster object from package snow. See snow integration for details and a simple example.
whitelist a data frame with two columns (optionally labeled "from" and "to"), containing a set of arcs to be included in the graph.
blacklist a data frame with two columns (optionally labeled "from" and "to"), containing a set of arcs not to be included in the graph.
test a character string, the label of the conditional independence test to be used in the algorithm. If none is specified, the default test statistic is the mutual information for discrete data sets and the linear correlation for continuous ones. See bnlearn-package for details.
alpha a numeric value, the target nominal type I error rate.
debug a boolean value. If TRUE a lot of debugging output is printed; otherwise the function is completely silent.
optimized a boolean value. See bnlearn-package for details.
strict a boolean value. If TRUE conflicting results in the learning process generate an error; otherwise they result in a warning.

Value

An object of class bn. See bn-class for details.

Author(s)

Marco Scutari

References

I. Tsamardinos, C. F. Aliferis, A. Statnikov. Time and sample efficient discovery of Markov blankets and direct causal relations. Proceedings of the Ninth International Conference on Knowledge Discovery and Data Mining KDD, pages 673-8, 2003.

I. Tsamardinos, L. E. Brown, C. Aliferis. The max-min hill-climbing Bayesian network learning algorithm. Machine Learning, 65(1), pages 31-78. Kluwer Academic Publishers, 2006.

See Also

gs, fast.iamb, iamb, inter.iamb, hc.


[Package bnlearn version 1.3 Index]