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Adaptive Sampling/Evidence
Method evidence record

Adaptive Sampling

Adaptive Cluster Sampling (ACS) is a probability-based survey design introduced by Steven K. Thompson in 1990 for estimating the abundance or total of rare, clustered populations. Starting from an initial random sample, the design adaptively adds neighboring units whenever a sampled unit satisfies a predefined condition—such as exceeding a count threshold—thereby concentrating sampling effort exactly where the population of interest occurs. It is most appropriate for ecologists, epidemiologists, and social scientists studying geographically or socially clustered rare phenomena.

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Adaptive Cluster Sampling
Taxonomic method record · process-pipeline / survey-methodology
  • Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. · DOI 10.1080/01621459.1990.10474975
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Related methods

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Used in the same domainCapture-Recapturemachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRespondent-Driven Samplingmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketStratified Samplingmachine-suggested · Relational suggestion, not evidence.

Evidence status

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Sources

1 recorded citation, copied from the method source record.

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