library(Benchmarking)
> A=array(c(50,40,20,30,40,35,20,30,20,30,12,12,15,28,10,18,
+ 50,48,25,40,35,50,20,50,30,32,13,25,20,30,11,30,
+ 45,50,30,40,40,45,28,45,32,35,15,30,25,30,12,38),dim=c(4,4,3))
>
> tse_1=dea(A[,c(1,2),1],A[,c(3,4),1],RTS="crs",ORIENTATION="in")
> A #頭兩列是投入,後兩列是產出
, , 1
[,1] [,2] [,3] [,4]
[1,] 50 40 20 15
[2,] 40 35 30 28
[3,] 20 20 12 10
[4,] 30 30 12 18
, , 2
[,1] [,2] [,3] [,4]
[1,] 50 35 30 20
[2,] 48 50 32 30
[3,] 25 20 13 11
[4,] 40 50 25 30
, , 3
[,1] [,2] [,3] [,4]
[1,] 45 40 32 25
[2,] 50 45 35 30
[3,] 30 28 15 12
[4,] 40 45 30 38
> tse_2=dea(A[,c(1,2),2],A[,c(3,4),2],RTS="crs",ORIENTATION="in")
> tse_3=dea(A[,c(1,2),3],A[,c(3,4),3],RTS="crs",ORIENTATION="in")
> TSE=cbind(tse_1$eff,tse_2$eff,tse_3$eff);TSE
[,1] [,2] [,3]
[1,] 0.5833333 1.0000000 1.0000000
[2,] 1.0000000 1.0000000 1.0000000
[3,] 0.8000000 0.9288462 0.6959607
[4,] 0.8571429 1.0000000 1.0000000
>
>
> iei_1_2=dea(A[,c(1,2),1],A[,c(3,4),1],XREF=A[,c(1,2),2],YREF=A[,c(3,4),2],RTS="crs",ORIENTATION="in")
> iei_1_3=dea(A[,c(1,2),1],A[,c(3,4),1],XREF=A[,c(1,2),3],YREF=A[,c(3,4),3],RTS="crs",ORIENTATION="in")
> iei_2_3=dea(A[,c(1,2),2],A[,c(3,4),2],XREF=A[,c(1,2),3],YREF=A[,c(3,4),3],RTS="crs",ORIENTATION="in")
> IEI=cbind(iei_1_2$eff,iei_1_3$eff,iei_2_3$eff);IEI
[,1] [,2] [,3]
[1,] 0.6456693 0.6250000 1.0714286
[2,] 1.3340659 1.1362126 0.9054594
[3,] 0.9111111 0.8225806 0.8323529
[4,] 1.0000000 0.7105263 0.8333333
上述是我之前用來練習的麥氏DEA的代碼,投入產出資料是A矩陣,共有三個時期,四個DMU,使用r套件為Benchmarking,未處理到MI的計算,但MI就是TSE及IEI的比值罷了,查查公式就能計算。給您做參考。