deep_compute

For the computation of the complete decision model is necessary to establish the 
deep position of every node.

Provides functions for the creation, evaluation and test of decision models based in
Multi Attribute Utility Theory (MAUT). Can process and evaluate local risk aversion utilities
for a set of indexes, compute utilities and weights for the whole decision tree defining the
decision model and simulate weights employing Dirichlet distributions under addition constraints
in weights.
Also includes other rating analysis methods as for example the Colley, Offensive - Defensive
ratings and the ranking aggregation with Borda count.

Pedro Guarderas

Decision Models with Multi Attribute Utility Theory

Felipe Aguirre

Julio Andrade

Daniel Lagos

Andrés Lopez

Nelson Recalde

Edison Salazar

deep_compute function

<dl><dt>tree</dt>
<dd>igraph object representing the tree</dd></dl>

Arguments

Author

Compute the deep position of every node — deep_compute

<dl>

<dt>tree</dt>
<dd>igraph object representing the tree</dd>

</dl>

deep_compute: Compute the deep position of every node

Description

Usage

Value

Arguments

Author

See Also