est.shstrrs: Estimating the Shapley value based on structured simple...

In ShapDoE: Approximation of the Shapley Values Based on Experimental Designs

Estimating the Shapley value based on structured simple random sampling (StrRS)

Description

Estimating the Shapley value based on structured simple random sampling (StrRS)

Usage

est.shstrrs(d, n, val, ...)

Arguments

d	an integer, the number of players.
n	an integer, the sample size.
val	the predefined value function.
...	other parameters used in val(sets,...).

Value

a vector including estimated Shapley values of all players based on StrRS.

Examples

temp_adjacent<-matrix(0,nrow=8,ncol=8)
temp_adjacent[1,6:8]<-1;temp_adjacent[2,7]<-1;temp_adjacent[c(4,6,7),8]<-1;
temp_adjacent<-temp_adjacent+t(temp_adjacent)
temp_val<-function(sets,adjacent){
  if(length(sets)==1) val<-0
  else{
    subadjacent<-adjacent[sets,sets]
    nsets<-length(sets)
    A<-diag(1,nsets); B<-matrix(0,nsets,nsets)
    for(l in 1:(nsets-1)){
      A<-A%*%subadjacent
      B<-B+A
    }
    val<-ifelse(sum(B==0)>nsets,0,1)
  }
  return(val)
}
est.shstrrs(8,112,temp_val,temp_adjacent)

ShapDoE documentation built on May 29, 2024, 11:24 a.m.