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On Integrated L1 Convergence Rate of an Isotonic Regression Estimator for Multivariate Observations
Fokianos, Konstantinos; Leucht, Anne; Neumann, Michael H. (2020): On Integrated L1 Convergence Rate of an Isotonic Regression Estimator for Multivariate Observations, in: IEEE Transactions on Information Theory, IEEE, Jg. 66, Nr. 10, S. 6389–6402, doi: 10.1109/TIT.2020.3013390.
Faculty/Chair:
Title of the Journal:
IEEE Transactions on Information Theory
Publisher Information:
Year of publication:
2020
Volume:
66
Issue:
10
Pages:
Language:
English
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:
RVK Classification:
Peer Reviewed:
Yes:
International Distribution:
Yes:
Type:
Article
Activation date:
October 5, 2020
Versioning
Question on publication
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https://fis.uni-bamberg.de/handle/uniba/48776