Sim.Weights: Simulation of weights

In mau: Decision Models with Multi Attribute Utility Theory

Description

Simulation of weights employing the Dirichlet distribution. The concentration parameters for the Dirichlet distribution are tentative weights.

Usage

Sim.Weights(n, utilities, alpha)

Arguments

n	number of simulations
utilities	utility dataframe, first column is the identifier
alpha	concentration parameter for the Dirichlet distribution

Details

Taking advantage of the Dirichlet distribution properties, the weights could be simulated with a concentration around given weights.

Value

List with data.frames {simulation, weights} with total utilities and simulated weights

Author(s)

Pedro Guarderas [e-mail]

See Also

Eval.Utilities

Examples

library( data.table )
N<-10
utilities<-data.table( id = 1:N, 
                       u1 = runif( N, 0, 1 ), 
                       u2 = runif( N, 0, 1 ), 
                       u3 = runif( N, 0, 1 ),
                       u4 = runif( N, 0, 1 ) )
n<-100
alpha<-c( 0.2, 0.5, 0.1, 0.2 )
S<-Sim.Weights( n, utilities, alpha )

Example output

mau documentation built on May 1, 2019, 8:23 p.m.