A mixture- based framework for nonparametric density estimation
The primary goal of this thesis is to provide a mixture-based framework for nonparametric density estimation. This framework advocates the use of a mixture model with a nonparametric mixing distribution to approximate the distribution of the data. The implementation of a mixture-based nonparametric...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
New Zealand: University of Auckland
2012
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| Subjects: | |
| Online Access: | http://hdl.handle.net/123456789/1621 |
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| Summary: | The primary goal of this thesis is to provide a mixture-based framework for nonparametric density estimation. This framework advocates the use of a mixture
model with a nonparametric mixing distribution to approximate the distribution of the data. The implementation of a mixture-based nonparametric density estimator
generally requires the specification of parameters in a mixture model and the choice of the bandwidth parameter. Consequently, a nonparametric methodology consisting of both the estimation and selection steps is described. |
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