ci_rbod_spatial function

Spatial robust Benefit of the Doubt approach (Sp-RBoD)

The Spatial robust Benefit of the Doubt approach (Sp-RBoD) method allows to take into account the spatial contextual condition into the robust Benefit of the Doubt method.

ci_rbod_spatial(x, indic_col, M=20, B=100, W)

Arguments

• x: A data.frame containing score of the simple indicators.
• indic_col: Simple indicators column number.
• M: The number of elements in each of the bootstrapped samples; default is 20.
• B: The number of bootstrap replicates; default is 100.
• W: The spatial weights matrix. A square non-negative matrix with no NAs representing spatial weights; may be a matrix of class "sparseMatrix" (spdep package)

Returns

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

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

References

Fusco E., Vidoli F., Sahoo B.K. (2018) "Spatial heterogeneity in composite indicator: a methodological proposal", Omega, Vol. 77, pp. 1-14

Author(s)

Fusco E., Vidoli F.

See Also

ci_rbod

Examples

data(EU_NUTS1)

coord = EU_NUTS1[,c("Long","Lat")]
k<-knearneigh(as.matrix(coord), k=5)
k_nb<-knn2nb(k)
W_mat <-nb2mat(k_nb,style="W",zero.policy=TRUE)

CI = ci_rbod_spatial(EU_NUTS1,c(2:3),M=10,B=20, W=W_mat)