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Projekt
Efficient nonparametric regression when the support is bounded
Antragsteller
Professor Dr. Holger Drees; Professor Dr. Markus Reiß
Fachliche Zuordnung
Mathematik
Förderung
Förderung von 2012 bis 2020
Projektkennung
Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 197645397
If in nonparametric regression the support of the error distribution has a sharp boundary, then the regression function and functionals thereof can be estimated with a higher rate of convergence than in regular models. We examine the geometry of such irregular statistical experiments and develop efficient statistical procedures that adapt both to the smoothness of the regression functionand to the degree of irregularity of the error distribution. Moreover, goodness-of-fit tests for the model assumptions will be constructed and concrete estimation procedures for order-book data will be developed.
DFG-Verfahren
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