Item type:Thesis, Open Access

Nonparametric estimation in models for unobservable heterogeneity

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Philipps-Universität Marburg

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Abstract

Nonparametric models which allow for data with unobservable heterogeneity are studied. The first publication introduces new estimators and their asymptotic properties for conditional mixture models. The second publication considers estimation of a function from noisy observations of its Radon transform in a Gaussian white noise model.

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Hohmann, Daniel (131354507): Nonparametric estimation in models for unobservable heterogeneity. : Philipps-Universität Marburg 2014-03-18. DOI: https://doi.org/10.17192/z2014.0117.

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This item has been published with the following license: In Copyright