impute

impute,BNDataset-method

impute,BNDataset

Impute a <code>BNDataset</code> raw data with missing values.

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

impute function

<dl><dt>object</dt>
<dd>the <code>BNDataset</code> object.</dd>
<dt>k.impute</dt>
<dd>number of neighbours to be used; for discrete variables we use mode,
for continuous variables the median value is instead taken.</dd></dl>

Arguments

Impute a BNDataset raw data with missing values. — impute

<dl>

<dt>object</dt>
<dd>the <code>BNDataset</code> object.</dd>


<dt>k.impute</dt>
<dd>number of neighbours to be used; for discrete variables we use mode,
for continuous variables the median value is instead taken.</dd>

</dl>

impute: Impute a `BNDataset` raw data with missing values.

Description

Usage

Arguments

Examples