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On Integrated L1 Convergence Rate of an Isotonic Regression Estimator for Multivariate Observations
Fokianos, Konstantinos; Leucht, Anne; Neumann, Michael H. (2022): On Integrated L1 Convergence Rate of an Isotonic Regression Estimator for Multivariate Observations, in: Bamberg: Otto-Friedrich-Universität, S. 1–35, doi: 10.20378/irb-55002.
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Year of publication:
2022
Pages:
Source/Other editions:
IEEE Transactions on Information Theory. - 66 (2020) 10
Year of first publication:
2020
Language:
English
DOI:
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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
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RVK Classification:
Type:
Preprint
Activation date:
February 3, 2023
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https://fis.uni-bamberg.de/handle/uniba/55002