mau (version 0.1.2)

Sim.Const.Weights: Simulation of constrained weights

Description

Simulation of weights employing the Dirichlet distribution. The concentration parameters for the Dirichlet distribution are tentative weights, additionally constraints over partial sums of weights are introduced by a list ordered structure.

Usage

Sim.Const.Weights(n, utilities, alpha, constraints)

Arguments

n

number of simulations

utilities

utility dataframe, first column is the identifier

alpha

concentration parameter for the Dirichlet distribution

constraints

list of sum constraints

Value

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

Details

Employing the properties of the Dirichlet distribution, weights could be simulated with a given concentration, additionally this simulation can be carry out by subsets of weights only to meet specific constraints.

See Also

Eval.Utilities

Examples

# NOT RUN {
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 )
constraints<-list( list( c(1,2), 0.7 ), 
                   list( c(3,4), 0.3 ) )
S<-Sim.Const.Weights( n, utilities, alpha, constraints )
plot.S<-Plot.Simulation.Weight( S$simulation, title = 'Simulations', 
                                xlab = 'ID', ylab = 'Utility' ) 
plot( plot.S )
# }