Additive isotone regression

dc.creatorMammen, Enno
dc.creatorYu, Kyusang
dc.date2007-09-06
dc.date.accessioned2026-07-07T08:28:40Z
dc.date.available2026-07-07T08:28:40Z
dc.descriptionThis paper is about optimal estimation of the additive components of a nonparametric, additive isotone regression model. It is shown that asymptotically up to first order, each additive component can be estimated as well as it could be by a least squares estimator if the other components were known. The algorithm for the calculation of the estimator uses backfitting. Convergence of the algorithm is shown. Finite sample properties are also compared through simulation experiments.
dc.descriptionPublished at http://dx.doi.org/10.1214/074921707000000355 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0709.0888
dc.identifierhttp://arxiv.org/abs/0709.0888
dc.identifierIMS Lecture Notes Monograph Series 2007, Vol. 55, 179-195
dc.identifierdoi:10.1214/074921707000000355
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/137699
dc.subjectStatistics Theory
dc.subject62G07, 62G20 (Primary)
dc.titleAdditive isotone regression
dc.typetext

Files

Collections