generate_models

emat_saturated_model

model_saturated

model_random_tree

model_rectangular_grid

model_line

model_star

model_loop

model_random

Models are represented in various forms

Provides the following types of models: Models for contingency
tables (i.e. log-linear models) Graphical Gaussian models for multivariate
normal data (i.e. covariance selection models) Mixed interaction models.
Documentation about 'gRim' is provided by vignettes included in this
package and the book by Højsgaard, Edwards and Lauritzen (2012,
<doi:10.1007/978-1-4614-2299-0>); see 'citation("gRim")' for details.

Søren Højsgaard

gRim

Graphical Interaction Models

generate_models function

<dl><dt>index</dt>
<dd>A vector of integers</dd>
<dt>type</dt>
<dd>Output type.</dd>
<dt>nms</dt>
<dd>Names of variables.</dd>
<dt>prob</dt>
<dd>Probability of any edge being present.</dd>
<dt>dim</dt>
<dd>A vector with dimensions</dd></dl>

Arguments

Generate various grapical models — generate_models

<dl>

<dt>index</dt>
<dd>A vector of integers</dd>


<dt>type</dt>
<dd>Output type.</dd>


<dt>nms</dt>
<dd>Names of variables.</dd>


<dt>prob</dt>
<dd>Probability of any edge being present.</dd>


<dt>dim</dt>
<dd>A vector with dimensions</dd>

</dl>

Generate various grapical models

generate_models: Generate various grapical models

Description

Usage

Arguments