grain_compile

compile.grain

compile.cpt_grain

compile.pot_grain

Compiles a Bayesian network. This means creating a
junction tree and establishing clique potentials.

models

utilities

Probability propagation in Bayesian networks, also known as graphical independence networks. Documentation
of the package is provided in vignettes included in the package and in
the paper by Højsgaard (2012, <doi:10.18637/jss.v046.i10>).
See 'citation("gRain")' for details.

Søren Højsgaard

gRain

Bayesian Networks

grain_compile function

<dl><dt>object</dt>
<dd>A grain object.</dd>
<dt>propagate</dt>
<dd>If TRUE the network is also propagated meaning
that the cliques of the junction tree are calibrated to each
other.</dd>
<dt>tug</dt>
<dd>A triangulated undirected graph.</dd>
<dt>root</dt>
<dd>A set of variables which must be in the root of the
junction tree</dd>
<dt>control</dt>
<dd>Controlling the compilation process.</dd>
<dt>details</dt>
<dd>For debugging info. Do not use.</dd>
<dt>...</dt>
<dd>Currently not used.</dd></dl>

Arguments

Søren Højsgaard, <a href="/link/sorenh%40math.aau.dk?package=gRain&version=1.4.5" data-mini-rdoc="gRain::sorenh@math.aau.dk">sorenh@math.aau.dk</a>

Author

Compile Bayesian network. — grain_compile

<dl>

<dt>object</dt>
<dd>A grain object.</dd>


<dt>propagate</dt>
<dd>If TRUE the network is also propagated meaning
that the cliques of the junction tree are calibrated to each
other.</dd>


<dt>tug</dt>
<dd>A triangulated undirected graph.</dd>


<dt>root</dt>
<dd>A set of variables which must be in the root of the
junction tree</dd>


<dt>control</dt>
<dd>Controlling the compilation process.</dd>


<dt>details</dt>
<dd>For debugging info. Do not use.</dd>


<dt>...</dt>
<dd>Currently not used.</dd>

</dl>

Søren Højsgaard, <a href='mailto:sorenh@math.aau.dk'>sorenh@math.aau.dk</a>

grain_compile: Compile Bayesian network.

Description

Usage

Value

Arguments

Author

References

See Also