ci_rbod_spatial {Compind}

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

Description

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.

Usage

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)

Value

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".

Author(s)

Fusco E., Vidoli F.

References

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

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)