Decision Models with Multi Attribute Utility Theory
Bar plot of utilities
Evaluation of decision tree nodes
Compute the deep position of every node
Divide weights of internal nodes
Evaluate utilities
Compute leaves weights
Evaluate utilities
mau
Plot decision MAUT model with weights simulations
Evaluate utilities
Read utilities
Simulation of constrained weights
Simulation of weights
Spider plot
Standardize strings
Sum weights for internal nodes
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.