ci_wroclaw: Wroclaw Taxonomic Method In Compind: Composite Indicators Functions

Description

Wroclaw taxonomy method (also known as the dendric method), originally developed at the University of Wroclaw, is based on the distance from a theoretical unit characterized by the best performance for all indicators considered; the composite indicator is therefore based on the sum of euclidean distances from the ideal unit and normalized by a measure of variability of these distance (mean + 2*std).

Usage

 `1` ```ci_wroclaw(x,indic_col) ```

Arguments

 `x` A data.frame containing simple indicators. `indic_col` Simple indicators column number.

Details

Please pay attention that ci_wroclaw_est is the distance from the "ideal" unit; so, units with higher values for the simple indicators get lower values of composite indicator.

Value

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

 `ci_wroclaw_est` Composite indicator estimated values. `ci_method` Method used; for this function ci_method="wroclaw".

Vidoli F.

References

UNESCO, "Social indicators: problems of definition and of selection", Paris 1974.

Mazziotta C., Mazziotta M., Pareto A., Vidoli F., "La sintesi di indicatori territoriali di dotazione infrastrutturale: metodi di costruzione e procedure di ponderazione a confronto", Rivista di Economia e Statistica del territorio, n.1, 2010.

`ci_bod`, `ci_mpi`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```i1 <- seq(0.3, 0.5, len = 100) - rnorm (100, 0.2, 0.03) i2 <- seq(0.3, 1, len = 100) - rnorm (100, 0.2, 0.03) Indic = data.frame(i1, i2) CI = ci_wroclaw(Indic) data(EU_NUTS1) CI = ci_wroclaw(EU_NUTS1,c(2:3)) data(EU_2020) data_selez = EU_2020[,c(1,22,191)] data_norm = normalise_ci(data_selez,c(2:3),c("POS","NEG"),method=3) ci_wroclaw(data_norm\$ci_norm,c(1:2)) ```