fs_construct {FuzzyPovertyR} | R Documentation |
Step 7. Constructs the fuzzy supplementary poverty measure based on Steps1-6.
fs_construct(steps4_5, weight, alpha, breakdown = NULL)
steps4_5 |
The results from |
weight |
A numeric vector of sampling weights. if NULL simple random sampling weights will be used |
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)
step2 = fs_transform(eusilc[,4:23], weight = eusilc$DB090, ID = eusilc$ID)
dimensions = c(1,1,1,1,2,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5)
steps4_5 = fs_weight(dimensions, step2 = step2, rho = NULL)
alpha <- fs_equate(steps4_5 = steps4_5,
weight = eusilc$DB090, HCR = .16, interval = c(1,10))
fs_results = fs_construct(steps4_5 = steps4_5,
weight = eusilc$DB090, alpha = alpha, breakdown = NULL)
fs_results = fs_construct(steps4_5 = steps4_5,
weight = eusilc$DB090, alpha = alpha, breakdown = eusilc$db040)