fs_construct_all {FuzzyPovertyR} | R Documentation |
Fuzzy supplementary poverty estimation.
fs_construct_all(
data,
weight = NULL,
ID = NULL,
dimensions,
rho = NULL,
HCR,
interval = c(1, 10),
alpha = NULL,
breakdown = NULL
)
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. |
dimensions |
A numeric vector (of length |
rho |
The critical value to be used for calculation of weights in the kendall correlation matrix. |
HCR |
The value of the head count ratio. |
interval |
A numeric vector of length two to look for the value of alpha (if not supplied). |
alpha |
The value of the exponent in equation $E(mu)^(alpha-1) = HCR$. If NULL it is calculated so that it equates the expectation of the membership function to HCR. |
breakdown |
A Dimension of sub-domains to calculate estimates for (using the same alpha). If numeric will be coerced to a Dimension. |
An object of class FuzzySupplementary containing the fuzzy membership function for each unit, the point estimate (i.e. the expected value of the function), and the alpha parameter.
data("eusilc")
FS <- fs_construct_all(data = eusilc[,4:23], weight = eusilc$DB090, # step 2
dimensions = c(1,1,1,1,2,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5), # step 3
rho = NULL, # steps 4 and 5
HCR = .12, # step 6
breakdown = eusilc$db040) # step 7 with breakdowns
summary(FS)
plot(FS)