Considering a non-polynomial basis for local kernel regression problem
A common used as solution for local kernel nonparametric regression problem is given using polynomial regression. In this study, we demonstrated the estimator and properties using maximum likelihood estimator for a non-polynomial basis such B-spline to replacing the polynomial basis. This estimator...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
AIP Publishing
2016
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| Online Access: | http://psasir.upm.edu.my/id/eprint/57323/ http://psasir.upm.edu.my/id/eprint/57323/1/Considering%20a%20non-polynomial%20basis%20for%20local%20kernel%20regression%20problem.pdf |
| Summary: | A common used as solution for local kernel nonparametric regression problem is given using polynomial regression. In this study, we demonstrated the estimator and properties using maximum likelihood estimator for a non-polynomial basis such B-spline to replacing the polynomial basis. This estimator allows for flexibility in the selection of a bandwidth and a knot. The best estimator was selected by finding an optimal bandwidth and knot through minimizing the famous generalized validation function. |
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