ci_bod_constr {Compind} R Documentation

## 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.

`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)
```

[Package Compind version 2.2 Index]