ci_geom_gen {Compind} R Documentation

## Generalized geometric mean quantity index numbers

### Description

This function use the geometric mean to aggregate the single indicators. Two weighting criteria has been implemented: EQUAL: equal weighting and BOD: Benefit-of-the-Doubt weights following the Puyenbroeck and Rogge (2017) approach.

### Usage

ci_geom_gen(x,indic_col,meth,up_w,low_w,bench)

### Arguments

 x A data.frame containing simple indicators. indic_col A numeric list indicating the positions of the simple indicators. meth "EQUAL" = Equal weighting set, "BOD" = Benefit-of-the-Doubt weighting set. up_w if meth="BOD"; upper bound of the weighting set. low_w if meth="BOD"; lower bound of the weighting set. bench Row number of the benchmark unit used to normalize the data.frame x.

### Value

An object of class "CI". This is a list containing the following elements:

If meth = "EQUAL":

• ci_mean_geom_est: Composite indicator estimated values.

• ci_method: Method used; for this function ci_method="mean_geom".

If meth = "BOD":

• ci_geom_bod_est: Constrained composite indicator estimated values.

• ci_geom_bod_weights: Raw constrained weights assigned to the simple indicators.

• ci_method: Method used; for this function ci_method="geometric_bod".

### Author(s)

Rogge N., Vidoli F.

### References

Van Puyenbroeck T. and Rogge N. (2017) "Geometric mean quantity index numbers with Benefit-of-the-Doubt weights", European Journal of Operational Research, Volume 256, Issue 3, Pages 1004 - 1014

ci_bod_dir,ci_bod

### Examples

i1 <- seq(0.3, 1, len = 100) - rnorm (100, 0.1, 0.03)
i2 <- seq(0.3, 0.5, len = 100) - rnorm (100, 0.1, 0.03)
i3 <- seq(0.3, 0.5, len = 100) - rnorm (100, 0.1, 0.03)
Indic = data.frame(i1, i2,i3)

geom1 = ci_geom_gen(Indic,c(1:3),meth = "EQUAL")
geom1$ci_mean_geom_est geom1$ci_method

geom2 = ci_geom_gen(Indic,c(1:3),meth = "BOD",0.7,0.3,100)
geom2$ci_geom_bod_est geom2$ci_geom_bod_weights



[Package Compind version 2.8 Index]