AlphaEdgeInternal

numeric - It indicates the level in the event tree.

level

Stratified.event.tree - S4 object that represents an event tree.

stratified.event.tree

numeric - It plays a role of a phantom sample to construct 
the prior probability distribution of a situation associated
with a particular variable in the event tree.

alpha

<code>AlphaEdgeInternal</code> yields a possible objective prior distribution for each situation
associated with a particular variable in the event tree.

Create and learn Chain Event Graph (CEG) models using a Bayesian
framework. It provides us with a Hierarchical Agglomerative algorithm to
search the CEG model space.
The package also includes several facilities for visualisations of the
objects associated with a CEG. The CEG class can represent a range of
relational data types, and supports arbitrary vertex, edge and graph
attributes. A Chain Event Graph is a tree-based graphical model that
provides a powerful graphical interface through which domain experts can
easily translate a process into sequences of observed events using plain
language. CEGs have been a useful class of graphical model especially to
capture context-specific conditional independences. References: Collazo R,
Gorgen C, Smith J. Chain Event Graph. CRC Press, ISBN 9781498729604, 2018
(forthcoming); and Barday LM, Collazo RA, Smith JQ, Thwaites PA, Nicholson AE.
The Dynamic Chain Event Graph. Electronic Journal of Statistics, 9 (2) 2130-2169
<doi:10.1214/15-EJS1068>.

AlphaEdgeInternal: AlphaEdgeInternal

Description

Usage

Arguments

Value