ci_geom_gen function

Generalized geometric mean quantity index numbers

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.

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.

Returns

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".

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

Author(s)

Rogge N., Vidoli F.

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