binve

Inverts a marginal log-linear parametrization.

marginal log-linear models

discrete data

Provides functions for defining
mixed graphs containing three types of edges, directed,
undirected and bi-directed, with possibly multiple edges.
These graphs are useful because they capture fundamental
independence structures in multivariate distributions
and in the induced distributions after marginalization
and conditioning.
The package is especially concerned with Gaussian graphical
models for
(i) ML estimation for directed acyclic graphs, undirected and
bi-directed graphs and ancestral graph models
(ii) testing several conditional independencies
(iii) checking global identification of DAG Gaussian models
with one latent variable
(iv) testing Markov equivalences and generating Markov
equivalent graphs of specific types.

Giovanni M Marchetti

Graphical Markov Models with Mixed Graphs

Giovanni M. Marchetti

Mathias Drton

Kayvan Sadeghi

binve function

<dl> <dt>eta</dt>
<dd>a vector of dimension <code>t-1</code> where <code>t</code> is the number of cells
of a contingency table.</dd> <dt>C</dt>
<dd>A contrast matrix.</dd> <dt>M</dt>
<dd>A marginalization matrix.</dd> <dt>G</dt>
<dd>G is the model matrix of the loglinear parameterization with no constant term.</dd> <dt>maxit</dt>
<dd>an integer, specifying the maximum number of iterations. Default 500.</dd> <dt>print</dt>
<dd>a logical value: if <code>TRUE</code>, prints the criterion after each cycle.</dd> <dt>tol</dt>
<dd>A small value specifying the tolerance for the convergence criterion. Default:
<code>1e-10</code>.</dd></dl>

Arguments

Antonio Forcina, Giovanni M. Marchetti

Author

Inverts a marginal log-linear parametrization — binve

<dl>

 <dt>eta</dt>
<dd>a vector of dimension <code>t-1</code> where <code>t</code> is the number of cells
of a contingency table.</dd>

 <dt>C</dt>
<dd>A contrast matrix.</dd>

 <dt>M</dt>
<dd>A marginalization matrix.</dd>

 <dt>G</dt>
<dd>G is the model matrix of the loglinear parameterization with no constant term.</dd>

 <dt>maxit</dt>
<dd>an integer, specifying the maximum number of iterations. Default 500.</dd>

 <dt>print</dt>
<dd>a logical value: if <code>TRUE</code>, prints the criterion after each cycle.</dd>

 <dt>tol</dt>
<dd>A small value specifying the tolerance for the convergence criterion. Default:
<code>1e-10</code>.</dd>

</dl>

binve: Inverts a marginal log-linear parametrization

Description

Usage

Value

Arguments

Author

Details

References

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