Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4967893 | Journal of Computational Physics | 2016 | 16 Pages |
Abstract
We present a sampling strategy of least squares polynomial regression. The strategy combines two recently developed methods for least squares method: Christoffel least squares algorithm and quasi-optimal sampling. More specifically, our new strategy first choose samples from the pluripotential equilibrium measure and then re-order the samples by the quasi-optimal algorithm. A weighted least squares problem is solved on a (much) smaller sample set to obtain the regression result. It is then demonstrated that the new strategy results in a polynomial least squares method with high accuracy and robust stability at almost minimal number of samples.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Yeonjong Shin, Dongbin Xiu,