Nonparametric estimation in models for unobservable heterogeneity

Nonparametric estimation in models for unobservable heterogeneity

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 transf...

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Gorde:
Xehetasun bibliografikoak
Egile nagusia: Hohmann, Daniel
Beste egile batzuk: Holzmann, Hajo (Prof. Dr.) (Tesi aholkularia)
Formatua: Dissertation
Hizkuntza:ingelesa
Argitaratua: Philipps-Universität Marburg 2014
Gaiak:
Radontransformation
limited-angle-Problem
Asymptotic properties
asymptotische Normalität
Mischung <Mathematik>
mixture model
random-coefficient-Modell
Estimation
asymptotic normality
Mischungsmodell
Radon transform
limited angle problem
nichtparametrisches Schätzen
efficient estimation
Mathematik
random coefficient model
Radon-Transformation
Nichtparametrische Schätzung
nonparametric estimation
Mathematics
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Deskribapena
Gaia: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.
DOI:10.17192/z2014.0117

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