sample.row

sample.row,BN-method

sample.row,BN

sample a row vector of values for a network.

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

sample.row function

<dl><dt>x</dt>
<dd>a <code>BN</code> or <code>InferenceEngine</code> object.</dd>
<dt>mar</dt>
<dd>fraction [0,1] of missing values in the sampled vector 
(missing at random), default value is 0 (no missing values).</dd></dl>

Arguments

sample a row vector of values for a network. — sample.row

<dl>

<dt>x</dt>
<dd>a <code>BN</code> or <code>InferenceEngine</code> object.</dd>


<dt>mar</dt>
<dd>fraction [0,1] of missing values in the sampled vector 
(missing at random), default value is 0 (no missing values).</dd>

</dl>

sample.row: sample a row vector of values for a network.

Description

Usage

Value

Arguments