uweights: Compute unit weights underlying the small area estimates or...

In hbsae: Hierarchical Bayesian Small Area Estimation

Compute unit weights underlying the small area estimates or their aggregate.

Description

The small area estimates can be interpreted as weighted sums of the response variable. This function computes the weights corresponding to the aggregated small area estimates or the weights corresponding to a specific small area estimate. The weights applied to the response variable need not exactly reproduce the Hierarchical Bayes estimate since the latter is averaged over the posterior distribution for the variance ratio whereas the weights are evaluated at the posterior mean. Under the default prior for the fixed effects, the weights applied to the design matrix reproduce the corresponding population numbers.

Usage

uweights(x, areaID = NULL, forTotal = FALSE)

Arguments

x	sae object.
areaID	if left unspecified (NULL), weights corresponding to the overall (aggregated) estimate are returned. Otherwise weights that reproduce the estimate for a specific area are returned.
forTotal	if FALSE weights will be divided by the corresponding population size.

Value

An object of class weights.

See Also

summary.weights, plot.weights

Examples

d <- generateFakeData()

# compute small area estimates
sae <- fSAE(y0 ~ x + area2, data=d$sam, area="area", popdata=d$Xpop,
            method="hybrid", keep.data=TRUE)

# compute unit weights
w <- uweights(sae, forTotal=TRUE)
summary(w)  # summary statistics
plot(w)  # histogram of weights
# checks
all.equal(sum(w * sae$y), sum(EST(sae) * sae$Narea))
all.equal(colSums(w * as.matrix(sae$X)), colSums(sae$Xp * sae$Narea))

hbsae documentation built on March 18, 2022, 6:34 p.m.