Line fitting
For a broader coverage related to this topic, see Curve fitting.
Line fitting is the process of constructing a straight line that has the best fit to a series of data points.
Several methods exist, considering, e.g.:
- Vertical distance: Simple linear regression
- Resistance to outliers: Robust simple linear regression
- Orthogonal distance: Orthogonal regression
- Weighted geometric distance: Deming regression
- Scale invariance: Major axis regression
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.).
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