pps {prnsamplr} | R Documentation |
Stratified probability-proportional-to-size sampling
Description
Stratified probability-proportional-to-size (Pareto PiPS) sampling using permanent random numbers. Can also be used for non-stratified Pareto PiPS using a dummy stratum taking the same value for each object.
Usage
pps(frame, stratid, nsamp, prn, size)
Arguments
frame |
Data frame (or data.table or tibble) containing the elements to sample from. |
stratid |
Variable in |
nsamp |
Variable in |
prn |
Variable in |
size |
Variable in |
Value
A copy of the input sampling frame together with the boolean variable
sampled
, indicating sample inclusion, as well as a numeric variable
lambda
containing the estimated first-order inclusion probabilities
and the numeric variable
Q = \frac{prn(1 - lambda)}{lambda(1 - prn)}
that determines which elements are sampled.
See Also
prnsamplr, samp, srs, transformprn, ExampleData
Examples
dfOut <- pps(
frame = ExampleData,
nsamp = ~nsample,
stratid = ~stratum,
prn = ~rands,
size = ~sizeM
)