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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