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SODA
1997
ACM

A Practical Approximation Algorithm for the LMS Line Estimator

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A Practical Approximation Algorithm for the LMS Line Estimator
The problem of fitting a straight line to a finite collection of points in the plane is an important problem in statistical estimation. Robust estimators are widely used because of their lack of sensitivity to outlying data points. The least median-of-squares (LMS) regression line estimator is among the best known robust estimators. Given a set of n points in the plane, it is defined to be the line that minimizes the median squared residual or, more generally, the line that minimizes the residual of any given quantile q, where
David M. Mount, Nathan S. Netanyahu, Kathleen Roma
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 1997
Where SODA
Authors David M. Mount, Nathan S. Netanyahu, Kathleen Romanik, Ruth Silverman, Angela Y. Wu
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