Local regression with meaningful parameters

Rafael A. Irizarry

doi:10.1198/000313001300339969

Local regression with meaningful parameters

Rafael A. Irizarry

Bloomberg School of Public Health

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Local regression, or loess, has become a popular method for smoothing scatterplots and for nonparametric regression in general. The final result is a "smoothed" version of the data. To obtain the value of the smooth estimate associated with a given covariate a polynomial, usually a line, is fitted locally using weighted least squares. This article presents a version of local regression that fits more general parametric functions. In certain cases, the fitted parameters may be interpreted in some way and we call them meaningful parameters. Examples are included that show how this procedure is useful for signal processing, physiological, and financial data.

Original language	English (US)
Pages (from-to)	72-79
Number of pages	8
Journal	American Statistician
Volume	55
Issue number	1
DOIs	https://doi.org/10.1198/000313001300339969
State	Published - Feb 2001

Keywords

Circadian pattern
Harmonic model
Local regression
Meaningful parameters
Sound analysis

ASJC Scopus subject areas

Statistics and Probability
General Mathematics
Statistics, Probability and Uncertainty

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10.1198/000313001300339969

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keywords = "Circadian pattern, Harmonic model, Local regression, Meaningful parameters, Sound analysis",

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Local regression with meaningful parameters

Abstract

Keywords

ASJC Scopus subject areas

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