distance_mat_stages

Compute the matrix of distances between probabilities,
e.g the transition probabilities for a given variable in a
staged event tree.

internal

Creates and fits staged event tree probability models,
which are probabilistic graphical models capable of representing
asymmetric conditional independence statements
for categorical variables.
Includes functions to create, plot and fit staged
event trees from data, as well as many efficient structure
learning algorithms.
References:
Carli F, Leonelli M, Riccomagno E, Varando G (2022).
<doi: 10.18637/jss.v102.i06>.
Collazo R. A., Görgen C. and Smith J. Q.
(2018, ISBN:9781498729604).
Görgen C., Bigatti A., Riccomagno E. and Smith J. Q. (2018)
<arXiv:1705.09457>.
Thwaites P. A., Smith, J. Q. (2017) <arXiv:1510.00186>.
Barclay L. M., Hutton J. L. and Smith J. Q. (2013)
<doi:10.1016/j.ijar.2013.05.006>.
Smith J. Q. and Anderson P. E. (2008)
<doi:10.1016/j.artint.2007.05.004>.

Gherardo Varando

stagedtrees

Staged Event Trees

Federico Carli

Manuele Leonelli

Eva Riccomagno

distance_mat_stages function

<dl><dt>x</dt>
<dd>list of conditional probabilities for each stage.</dd>
<dt>distance</dt>
<dd>the distance function e.g. <code>probdist.kl</code>.</dd></dl>

Arguments

Compute the distance matrix — distance_mat_stages

<dl>

<dt>x</dt>
<dd>list of conditional probabilities for each stage.</dd>


<dt>distance</dt>
<dd>the distance function e.g. <code>probdist.kl</code>.</dd>

</dl>

distance_mat_stages: Compute the distance matrix

Description

Usage

Value

Arguments