ci_mean_min function

Mean-Min Function

The Mean-Min Function (MMF) is an intermediate case between arithmetic mean, according to which no unbalance is penalized, and min function, according to which the penalization is maximum. It depends on two parameters that are respectively related to the intensity of penalization of unbalance ($\alpha$) and intensity of complementarity ($\beta$) among indicators.

ci_mean_min(x, indic_col, alpha, beta)

Arguments

• x: A data.frame containing simple indicators.
• indic_col: Simple indicators column number.
• alpha: The intensity of penalisation of unbalance among indicators, $0 \le \alpha \le 1$
• beta: The intensity of complementarity among indicators, $\beta \ge 0$

Returns

An object of class "CI". This is a list containing the following elements: - ci_mean_min_est: Composite indicator estimated values.

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

References

Casadio Tarabusi, E., & Guarini, G. (2013) "An unbalance adjustment method for development indicators", Social indicators research, 112(1), 19-45.

Author(s)

Vidoli F.

See Also

ci_mpi, normalise_ci

Examples

data(EU_NUTS1)
data_norm = normalise_ci(EU_NUTS1,c(2:3),c("NEG","POS"),method=2)
CI = ci_mean_min(data_norm$ci_norm, alpha=0.5, beta=1)