In this thesis, a binary decision tree is used as an approximation of a nonparametric regression curve. The best fitted decision tree is estimated from data via least squares method. It is investigated how and under which conditions the estimator converges.
These asymptotic results then are used to create asymptotic convergence regions.
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:73135 |
Date | 14 December 2020 |
Creators | Albrecht, Nadine |
Contributors | Ferger, Dietmar, Stute, Winfried, Technische Universität Dresden |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/publishedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
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