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Amostragem Aleatória Simples Adaptativa×Amostragem por Agrupamento Adaptativo×
ÁreaMetodologia de surveyMetodologia de survey
FamíliaProcess / pipelineProcess / pipeline
Ano de origem1990–19921990
Autor originalSteven K. ThompsonSteven K. Thompson
TipoProbability-based adaptive sampling designProbability-based adaptive sampling design
Fonte seminalThompson, S. K. (1992). Sampling. John Wiley & Sons. ISBN: 978-0471548850Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059. DOI ↗
Outros nomesASRS, adaptive SRS, adaptive random sampling, sequential adaptive samplingACS, adaptive network sampling, sequential cluster sampling, neighborhood adaptive sampling
Relacionados56
ResumoAdaptive 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.Adaptive cluster sampling (ACS) is a probability-based design in which an initial random sample of units triggers the inclusion of neighboring units whenever a predefined condition — typically a threshold count of a rare attribute — is satisfied. Developed by Steven K. Thompson in 1990, ACS is especially powerful for estimating the abundance or distribution of rare, spatially clustered populations such as endangered species, disease hotspots, or hard-to-reach social groups.
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ScholarGateComparar métodos: Adaptive Simple Random Sampling · Adaptive Cluster Sampling. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare