discreteness

discreteness,BN-method

discreteness,BN

discreteness,BNDataset-method

discreteness,BNDataset

Get a vector representing the status of the variables (with their names) of a <code>BN</code> or <code>BNDataset</code>.
Elements of the vector are <code>c</code> if the variable is continue, and <code>d</code> if the variable is discrete.

Bayesian Network Structure Learning from Data with Missing Values.
The package implements the Silander-Myllymaki complete search,
the Max-Min Parents-and-Children, the Hill-Climbing, the
Max-Min Hill-climbing heuristic searches, and the Structural
Expectation-Maximization algorithm. Available scoring functions are
BDeu, AIC, BIC. The package also implements methods for generating and using
bootstrap samples, imputed data, inference.

Alberto Franzin

bnstruct

Bayesian Network Structure Learning from Data with Missing
Values

Francesco Sambo

discreteness function

<dl><dt>x</dt>
<dd>an object.</dd></dl>

Arguments

get status (discrete or continuous) of the variables of an object. — discreteness

<dl>

<dt>x</dt>
<dd>an object.</dd>

</dl>

discreteness: get status (discrete or continuous) of the variables of an object.

Description

Usage

Value

Arguments