ci_bod_var_w function

Variance weighted Benefit of the Doubt approach (BoD variance weighted)

Variance weighted Benefit of the Doubt approach (BoD variance weighted) is a particular form of BoD method with additional information in the optimization problem. In particular it has been added weight constraints (in form of an Assurance region type I (AR I)) endogenously determined in order to take into account the ratio of the vertical variability of each simple indicator relative to one another.

ci_bod_var_w(x,indic_col,boot_rep = 5000)

Arguments

• x: A data.frame containing score of the simple indicators.
• indic_col: Simple indicators column number.
• boot_rep: The number of bootstrap replicates (default=5000) for the estimates of the nonparametric bootstrap (first order normal approximation) confidence intervals for the variances of the simple indicators.

Details

For more informations about the estimation of the confidence interval for the variances, please see function boot.ci, package boot.

Returns

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

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

References

Vidoli F., Mazziotta C. (2013) "Robust weighted composite indicators by means of frontier methods with an application to European infrastructure endowment", Statistica Applicata, Italian Journal of Applied Statistics.

Author(s)

Vidoli F.

See Also

ci_bod, ci_rbod

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_var_w(Indic)