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Line fitting
Index of articles associated with the same name From Wikipedia, the free encyclopedia
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Line fitting is the process of constructing a straight line that has the best fit to a series of data points.
 | This page is a primary topic and an article should be written about it. One or more editors believe it holds the title of a broad-concept article. The article may be written here or drafted elsewhere first. Related titles should be described here, while unrelated titles should be moved to Line fitting (disambiguation). (May 2019) |
Several methods exist, considering:
- Vertical distance: Simple linear regression
- Resistance to outliers: Robust simple linear regression
- Perpendicular distance: Orthogonal regression (this is not scale-invariant i.e. changing the measurement units leads to a different line.)
- Weighted geometric distance: Deming regression
- Scale invariant approach: Major axis regression This allows for measurement error in both variables, and gives an equivalent equation if the measurement units are altered.
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See also
Further reading
- "Fitting lines", chap.1 in LN. Chernov (2010), Circular and linear regression: Fitting circles and lines by least squares, Chapman & Hall/CRC, Monographs on Statistics and Applied Probability, Volume 117 (256 pp.).
- "Homogeneous Least-Squares Problem", Keijo Inkilä (2005), The Photogrammetric Journal of Finland, 19(2):34–42
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