Compind (version 3.2)

ci_geom_gen: 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)

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".

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.

Author

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

See Also

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