Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6421739 | Applied Mathematics and Computation | 2014 | 11 Pages |
Abstract
In the present paper, we propose and analyze a novel method for estimating a univariate regression function of bounded variation. The underpinning idea is to combine two classical tools in nonparametric statistics, namely isotonic regression and the estimation of additive models. A geometrical interpretation enables us to link this iterative method with Von Neumann's algorithm. Moreover, making a connection with the general property of isotonicity of projection onto convex cones, we derive another equivalent algorithm and go further in the analysis.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Arnaud Guyader, Nicolas Jégou, Alexander B. Németh, Sándor Z. Németh,