Classification of Nonparametric Regression Functions in Heterogeneous Panels
| dc.contributor.author | Vogt, Michael | |
| dc.contributor.author | Linton, Oliver B. | |
| dc.date.accessioned | 2015-07-15T09:45:23Z | |
| dc.date.available | 2015-07-15T09:45:23Z | |
| dc.date.issued | 2015 | eng |
| dc.description.abstract | We investigate a nonparametric panel model with heterogeneous regression functions. In a variety of applications, it is natural to impose a group structure on the regression curves. Specifically, we may suppose that the observed individuals can be grouped into a number of classes whose members all share the same regression function. We develop a statistical procedure to estimate the unknown group structure from the observed data. Moreover, we derive the asymptotic properties of the procedure and investigate its finite sample performance by means of a simulation study and a real-data example. | eng |
| dc.description.version | published | |
| dc.identifier.doi | 10.2139/ssrn.2567312 | eng |
| dc.identifier.uri | http://kops.uni-konstanz.de/handle/123456789/31431 | |
| dc.language.iso | eng | eng |
| dc.subject | Panel data, nonparametric regression, classification of regression curves | eng |
| dc.subject.ddc | 510 | eng |
| dc.title | Classification of Nonparametric Regression Functions in Heterogeneous Panels | eng |
| dc.type | PREPRINT | eng |
| dspace.entity.type | Publication | |
| kops.citation.bibtex | @unpublished{Vogt2015Class-31431,
year={2015},
doi={10.2139/ssrn.2567312},
title={Classification of Nonparametric Regression Functions in Heterogeneous Panels},
author={Vogt, Michael and Linton, Oliver B.}
} | |
| kops.citation.iso690 | VOGT, Michael, Oliver B. LINTON, 2015. Classification of Nonparametric Regression Functions in Heterogeneous Panels | deu |
| kops.citation.iso690 | VOGT, Michael, Oliver B. LINTON, 2015. Classification of Nonparametric Regression Functions in Heterogeneous Panels | eng |
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| temp.internal.duplicates | <p>Keine Dubletten gefunden. Letzte Überprüfung: 06.05.2015 10:42:19</p> | deu |