On Computing the Least Quantile of Squares Estimate
نویسنده
چکیده
In linear regression, an important role is played by the least quantile of squares (LQS) estimate, which involves the minimization of the qth smallest squared residual for a given set of data. This function is nondifferentiable and nonconvex and may have a large number of local minima. This paper is mainly concerned with the efficient calculation of the global solution, and some different approaches are considered.
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ورودعنوان ژورنال:
- SIAM J. Scientific Computing
دوره 19 شماره
صفحات -
تاریخ انتشار 1998