sample.dataset

sample.dataset,BN-method

sample.dataset,BN

sample.dataset,InferenceEngine-method

sample.dataset,InferenceEngine

sample a <code>BNDataset</code> from a network of an inference engine.

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.dataset function

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

Arguments

sample a BNDataset from a network of an inference engine. — sample.dataset

<dl>

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


<dt>n</dt>
<dd>number of items to sample.</dd>


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

</dl>

sample.dataset: sample a `BNDataset` from a network of an inference engine.

Description

Usage

Value

Arguments