On Integrated L1 Convergence Rate of an Isotonic Regression Estimator for Multivariate Observations
Faculty/Professorship: | Mathematics for Business and Economics |
Author(s): | Fokianos, Konstantinos; Leucht, Anne ![]() |
Title of the Journal: | IEEE Transactions on Information Theory |
Publisher Information: | IEEE |
Year of publication: | 2020 |
Volume: | 66 |
Issue: | 10 |
Pages: | 6389-6402 |
Language(s): | English |
DOI: | 10.1109/TIT.2020.3013390 |
Abstract: | We consider a general monotone regression estimation where we allow for independent and dependent regressors. We propose a modifcation of the classical isotonic least squares estimator and establish its rate of convergence for the integrated L1-loss function. Themethodology captures the shape of the data without assuming additivity or a parametricform for the regression function. Furthermore, the degree of smoothing is chosen automatically and no auxiliary tuning is required for the theoretical analysis. Some simulations and two real data illustrations complement the study of the proposed estimator. |
GND Keywords: | Isotone Regression; Methode der kleinsten Quadrate; Multivariate Analyse |
Keywords: | Isotonic least squares estimation, multivariate isotonic regression |
DDC Classification: | 330 Economics |
RVK Classification: | QH 170 |
Peer Reviewed: | Ja |
International Distribution: | Ja |
Type: | Article |
URI: | https://fis.uni-bamberg.de/handle/uniba/48776 |
Release Date: | 5. October 2020 |

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University of Bamberg