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Method evidence record

LOESS

LOESS (locally estimated scatterplot smoothing), introduced by William Cleveland in 1979 and extended with Susan Devlin in 1988, fits a smooth curve through data by performing a separate weighted polynomial regression in the neighbourhood of each point. Nearby observations count more than distant ones, so the method follows local structure without assuming any global functional form, making it a popular exploratory smoother for scatterplots.

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.

Local Regression (LOESS / LOWESS)

Taxonomic method recordml-modelmachine-learning

  1. Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association, 74(368), 829–836. · DOI 10.1080/01621459.1979.10481038

  2. Cleveland, W. S., & Devlin, S. J. (1988). Locally weighted regression: an approach to regression analysis by local fitting. Journal of the American Statistical Association, 83(403), 596–610. · DOI 10.1080/01621459.1988.10478639

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

Suggested3

Generated from the method graph and shown as machine-suggested relations. No evidence claim is inferred.