On Nonparametric Residual Variance Estimation

• DOI: 10.1007/s11063-008-9087-8
• Publication Date: 2008-10-25T06:27:02Z
• Authors: Elia Liitiäinen; Francesco Corona; Amaury Lendasse
• Keywords: 0101 mathematics; 01 natural sciences

In this paper, the problem of residual variance estimation is examined. The problem is analyzed in a general setting which covers non-additive heteroscedastic noise under non-iid sampling. To address the estimation problem, we suggest a method based on nearest neighbor graphs and we discuss its convergence properties under the assumption of a Holder continuous regression function. The universality of the estimator makes it an ideal tool in problems with only little prior knowledge available.