sim_data_from_dmrf

Simulate data from a decomposable discrete markov random field

Minimal and memory efficient implementation of the junction tree
algorithm using the Lauritzen-Spiegelhalter scheme;
S. L. Lauritzen and D. J. Spiegelhalter (1988)
<https://www.jstor.org/stable/2345762?seq=1>. The jti package is
part of the paper <doi:10.18637/jss.v111.i02>.

Mads Lindskou

Junction Tree Inference

sim_data_from_dmrf function

<dl><dt>graph</dt>
<dd>A decomposable discrete markov random field as an igraph object</dd>
<dt>lvls</dt>
<dd>Named integer vector where each element is the size of the
statespace of the corresponding variable</dd>
<dt>nsims</dt>
<dd>Number of simulations
distributions from which the simulatios are drawn.</dd>
<dt>increasing_prob</dt>
<dd>Logical. If true, probabilities in the underlying CPTs
increases with as the number of levels increses.</dd>
<dt>p1</dt>
<dd>Probability</dd>
<dt>p2</dt>
<dd>Probability</dd></dl>

Arguments

Simulate data from a decomposable discrete markov random field — sim_data_from_dmrf

<dl>

<dt>graph</dt>
<dd>A decomposable discrete markov random field as an igraph object</dd>


<dt>lvls</dt>
<dd>Named integer vector where each element is the size of the
statespace of the corresponding variable</dd>


<dt>nsims</dt>
<dd>Number of simulations
distributions from which the simulatios are drawn.</dd>


<dt>increasing_prob</dt>
<dd>Logical. If true, probabilities in the underlying CPTs
increases with as the number of levels increses.</dd>


<dt>p1</dt>
<dd>Probability</dd>


<dt>p2</dt>
<dd>Probability</dd>

</dl>

sim_data_from_dmrf: Simulate data from a decomposable discrete markov random field

Description

Usage

Arguments