| fs_transform {FuzzyPovertyR} | R Documentation |
Fuzzy supplementary poverty estimation
Description
Step 2. This function maps a set of answers to binary or categorical items to the (0,1) interval.
Usage
fs_transform(data, weight = NULL, ID = NULL, depr.score = "s", ...)
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. if NULL simple random sampling weights will be used |
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.
Value
An object of class FuzzySupplementary containing a matrix of the same dimension of data with items mapped into the (0,1) interval
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.
Examples
data(eusilc)
step2 = fs_transform(eusilc[,4:23], weight = eusilc$DB090, ID = eusilc$ID)