An object of class FuzzySupplementary containing a matrix of the same dimension of data with items mapped into the (0,1) interval
Arguments
data
A matrix or a data frame of identified items (see Step 1 of Betti et. al, 2018)
weight
A numeric vector of sampling weights of length nrow(step1). if NULL weights will set equal to n (n = sample size)
ID
A numeric or character vector of IDs. if NULL (the default) it is set as the row sequence
depr.score
The deprivation score to be used (see d or s in Betti et al (2018))
...
other parameters
Details
The function calculates deprivation score.
To obtain consistent measures of supplementary poverty it is important that items are in the right order.
Lower levels of the items have to correspond to more deprivation while higher levels of the items to a less deprivation.
References
Betti, G., Gagliardi, F., Lemmi, A., & Verma, V. (2015). Comparative measures of multidimensional deprivation in the European Union. Empirical Economics, 49(3), 1071-1100.
Betti, G., Gagliardi, F., & Verma, V. (2018). Simplified Jackknife variance estimates for fuzzy measures of multidimensional poverty. International Statistical Review, 86(1), 68-86.
#This example is based on the dataset eusilc included in the package#step 1 is the choice of the eusilc dataset#Step 2step2 = fs_transform(eusilc[,4:23], weight = eusilc$DB090, ID = eusilc$ID)