sevt_fit

an object of class <code>sevt</code>.

object

data.frame or contingency table with observations of
the variables in <code>object</code>.

data

smoothing parameter or pseudocount.

lambda

Estimate transition probabilities in a staged event tree from data.
Probabilities are estimated with the relative frequencies plus,
eventually, an additive (Laplace) smoothing.

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:
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

sevt_fit function

<dl><dt>object</dt>
<dd>an object of class <code>sevt</code>.</dd>
<dt>data</dt>
<dd>data.frame or contingency table with observations of
the variables in <code>object</code>.</dd>
<dt>lambda</dt>
<dd>smoothing parameter or pseudocount.</dd></dl>

Arguments

Fit a staged event tree — sevt_fit

<dl>

<dt>object</dt>
<dd>an object of class <code>sevt</code>.</dd>


<dt>data</dt>
<dd>data.frame or contingency table with observations of
the variables in <code>object</code>.</dd>


<dt>lambda</dt>
<dd>smoothing parameter or pseudocount.</dd>

</dl>

sevt_fit: Fit a staged event tree

Description

Usage

Value

Arguments

Details

Examples