Date of Award

8-2015

Document Type

Thesis

Degree Name

Master of Science (MS)

Legacy Department

Mathematical Science

Advisor

Luo, Jun

Committee Member

Gerard, Patrick

Committee Member

Bridges, William

Abstract

Nonparametric regression has been particularly well developed. Base on the asymptotic equivalence theory, there are some procedures that can turn more complicated nonparametric estimation problems into a standard nonparametric regression, especially in natural exponential families. This procedure is described in detail with a wavelet thresholding estimator for Gaussian nonparametric regression and simulation study shed light on the behavior of this method under different sample sizes and parameterizations of exponential distribution. The resulting estimators have a high degree of adaptivity in [2].

Included in

Mathematics Commons

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