ci_bod_constr_bad {Compind} | R Documentation |
The constrained Benefit of the Doubt function introduces additional constraints to the weight variation in the optimization procedure (Constrained Virtual Weights Restriction) allowing to restrict the importance attached to a single indicator expressed in percentage terms, ranging between a lower and an upper bound (VWR); this function, furthermore, allows to calculate the composite indicator simultaneously in presence of undesirable (bad) and desirable (good) indicators allowing to impose a preference structure (ordVWR).
ci_bod_constr_bad(x, indic_col, ngood=1, nbad=1, low_w=0, pref=NULL)
x |
A data.frame containing simple indicators; the order is important: first columns must contain the desirable indicators, while second ones the undesirable indicators. |
indic_col |
A numeric list indicating the positions of the simple indicators. |
ngood |
The number of desirable outputs; it has to be greater than 0. |
nbad |
The number of undesirable outputs; it has to be greater than 0. |
low_w |
Importance weights lower bound. |
pref |
The preference vector among indicators; For example if |
An object of class "CI". This is a list containing the following elements:
ci_bod_constr_bad_est |
Composite indicator estimated values. |
ci_method |
Method used; for this function ci_method="bod_constr_bad". |
ci_bod_constr_bad_weights |
Raw weights assigned to each simple indicator. |
ci_bod_constr_bad_target |
Indicator target values. |
Fusco E., Rogge N.
Rogge N., de Jaeger S. and Lavigne C. (2017) "Waste Performance of NUTS 2-regions in the EU: A Conditional Directional Distance Benefit-of-the-Doubt Model", Ecological Economics, vol.139, pp. 19-32.
Zanella A., Camanho A.S. and Dias T.G. (2015) "Undesirable outputs and weighting schemes in composite indicators based on data envelopment analysis", European Journal of Operational Research, vol. 245(2), pp. 517-530.
data(EU_2020)
indic <- c("employ_2011", "percGDP_2011", "gasemiss_2011","deprived_2011")
dat <- EU_2020[-c(10,18),indic]
# BoD Constrained VWR
CI_BoD_C = ci_bod_constr_bad(dat, ngood=2, nbad=2, low_w=0.05, pref=NULL)
CI_BoD_C$ci_bod_constr_bad_est
# BoD Constrained ordVWR
importance <- c("gasemiss_2011","percGDP_2011","employ_2011")
CI_BoD_C = ci_bod_constr_bad(dat, ngood=2, nbad=2, low_w=0.05, pref=importance)
CI_BoD_C$ci_bod_constr_bad_est