
A method is proposed for least absolute deviation curve fitting. It may be used to obtain least absolute deviations fits of general linear regressions. As a special case it includes a minor variant of a method for fitting straight lines by least absolute deviations that was previously thought to possess no generalization. The method has been tested on a computer and was found on a range of problems to execute in 1/4 to 1/20 of the cpu time required by a published algorithm based on linear programming.
linear regressions, Linear regression; mixed models, Numerical mathematical programming methods, Linear programming, Numerical smoothing, curve fitting, CPU time, Probabilistic methods, stochastic differential equations, least absolute deviations curve fitting, fitting straight lines
linear regressions, Linear regression; mixed models, Numerical mathematical programming methods, Linear programming, Numerical smoothing, curve fitting, CPU time, Probabilistic methods, stochastic differential equations, least absolute deviations curve fitting, fitting straight lines
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