ci_bod_constr {Compind}

Constrained Benefit of the Doubt approach (BoD)

Description

The constrained Benefit of the Doubt function lets to introduce additional constraints to the weight variation in the optimization procedure so that all the weights obtained are greater than a lower value (low_w) and less than an upper value (up_w).

Usage

ci_bod_constr(x,indic_col,up_w,low_w)

Arguments

x

A data.frame containing simple indicators.

indic_col

A numeric list indicating the positions of the simple indicators.

up_w

Importance weights upper bound.

low_w

Importance weights lower bound.

Value

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

ci_bod_constr_est

Constrained composite indicator estimated values.

ci_method

Method used; for this function ci_method="bod_constrained".

ci_bod_constr_weights

Raw constrained weights assigned to the simple indicators.

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.

See Also

ci_bod_dir,ci_bod

Examples

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_bod_constr(Indic,up_w=1,low_w=0.05)

data(EU_NUTS1)
data_norm = normalise_ci(EU_NUTS1,c(2:3),polarity = c("POS","POS"), method=2)
CI = ci_bod_constr(data_norm$ci_norm,c(1:2),up_w=1,low_w=0.05)