| point_estimator | R Documentation |
Each point that hits an establishment contributes y / expected_hits of
that establishment; the sum over hits is unbiased for the population total
whatever the number of times an establishment is hit (the more points fall
on an establishment, the larger its contribution, matching its larger
chance of selection). The variance is estimated at the cell level
(ultimate-cluster approximation): the cell contributions are treated as
cell totals and the variance estimator of the cell design is applied
(local-mean for "lpm", replicates for replicated systematic samples,
simple random sampling otherwise). With replicated systematic samples the
expected hits refer to the union of the replicates, so the replicate
variance is an approximation.
point_estimator(hits, sample)
hits |
Data frame with one row per point that hit an establishment:
columns |
sample |
The |
A one-row tibble as in design_variance(), with n_hits and
n_establishments.
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