Adaptive Simple Random Sampling
Adaptive simple random sampling (ASRS) begins with a conventional simple random sample and then expands the sample in regions where the variable of interest exceeds a pre-specified threshold. Units neighboring a qualifying observation are added to the sample, allowing the design to concentrate effort where the population is dense or rare, while retaining unbiased estimation through the Horvitz-Thompson or Hansen-Hurwitz estimators. The approach was systematized by Steven K. Thompson in the early 1990s as part of the broader adaptive sampling framework.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Thompson, S. K. (1992). Sampling. John Wiley & Sons. · ISBN 978-0471548850
- Thompson, S. K., & Seber, G. A. F. (1996). Adaptive Sampling. John Wiley & Sons. · ISBN 978-0471558712
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.