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Local regression

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Revision as of 07:11, 22 August 2024 by TDKR Chicago 101 (talk | changes) (Created page with "thumb|An example of a LOESS cruve '''Local regression''' or '''local polynomial regression''',{{sfn|Fox|Weisberg|2018|loc=Appendix}} also known as '''moving regression''',{{sfn|Harrell|2015|p=29}} is a general statement of the moving average and polynomial regression.{{sfn|Garimella|2017|p=}} It is used for scatterplot smoothing. They are also known as '''LOESS''' ('''locally estimated scatterplot smoothing''') and '''LOWESS''' (''...")
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An example of a LOESS cruve

Local regression or local polynomial regression,[1] also known as moving regression,[2] is a general statement of the moving average and polynomial regression.[3]

It is used for scatterplot smoothing. They are also known as LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced /ˈlɛs/ LOH-ess in this care. They are two strongly related non-parametric regression methods.

In some fields, LOESS is known and commonly known as Savitzky–Golay filter.[4][5]

References

  1. Fox & Weisberg 2018, Appendix.
  2. Harrell 2015, p. 29.
  3. Garimella 2017.
  4. "Savitzky–Golay filtering – MATLAB sgolayfilt". Mathworks.com.
  5. "scipy.signal.savgol_filter — SciPy v0.16.1 Reference Guide". Docs.scipy.org.