num.variables&lt;-

num.variables&lt;-,BNDataset-method

a <code><a rd-options="" href="/link/BNDataset?package=bnstruct&version=1.0.6" data-mini-rdoc="bnstruct::BNDataset">BNDataset</a></code> object.

number of variables of the dataset.

value

Set the number of variables observed in a dataset.

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

num.variables&lt;- function

a <code><a rd-options='' href='BNDataset'>BNDataset</a></code> object.

set number of variables of a <code><a rd-options='' href='BNDataset'>BNDataset</a></code>. — num.variables&lt;-

set number of variables of a <code><a rd-options='' href='BNDataset'>BNDataset</a></code>.

set number of variables of a <code><a rd-options="" href="/link/BNDataset?package=bnstruct&version=1.0.6" data-mini-rdoc="bnstruct::BNDataset">BNDataset</a></code>.

num.variables<-: set number of variables of a `BNDataset`.

Description

Usage

Arguments