Method evidence record
Adaptive Weighted Sampling
Adaptive weighted sampling is a probabilistic sampling procedure that assigns and iteratively updates inclusion weights for population units based on observed data collected during the sampling process itself. Unlike static weighted sampling — where weights are fixed before data collection from known auxiliary information — adaptive weighting revises probabilities as new information accumulates, concentrating sampling effort on units that contribute most to estimating the target quantity. It is used in survey methodology, simulation studies, and rare-event estimation.
Evidence statusSources recorded, not reviewedBibliographic sources are present. Claim-level evidence review has not been performed.
Source record
Recorded
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
Adaptive Weighted Sampling
Taxonomic method recordprocess-pipelinesurvey-methodology
Open full method2 recorded citations, copied from the method source record.
Curated claims
Assessed
Claims persisted in the evidence ledger, each with its own assessment.
No curated claims yet
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Related methods
Suggested6
Generated from the method graph and shown as machine-suggested relations. No evidence claim is inferred.
- Taxonomic bucketAdaptive Cluster Sampling
machine-suggestedRelational suggestion, not evidence.
- Same method familyImportance Sampling
machine-suggestedRelational suggestion, not evidence.
- Taxonomic bucketMultistage Sampling
machine-suggestedRelational suggestion, not evidence.
- Same method familyStratified Sampling
machine-suggestedRelational suggestion, not evidence.
- Taxonomic bucketSystematic Sampling
machine-suggestedRelational suggestion, not evidence.
- Taxonomic bucketWeighted Sampling
machine-suggestedRelational suggestion, not evidence.