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 |
| _version_ | 1848853333008187392 |
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| author | Silalahi, Divo Dharma Midi, Habshah |
| author_facet | Silalahi, Divo Dharma Midi, Habshah |
| author_sort | Silalahi, Divo Dharma |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-15T10:52:18Z |
| format | Conference or Workshop Item |
| id | upm-57323 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T10:52:18Z |
| publishDate | 2016 |
| publisher | AIP Publishing |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-573232017-09-26T04:04:41Z http://psasir.upm.edu.my/id/eprint/57323/ Considering a non-polynomial basis for local kernel regression problem Silalahi, Divo Dharma Midi, Habshah 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. AIP Publishing 2016 Conference or Workshop Item PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/57323/1/Considering%20a%20non-polynomial%20basis%20for%20local%20kernel%20regression%20problem.pdf Silalahi, Divo Dharma and Midi, Habshah (2016) Considering a non-polynomial basis for local kernel regression problem. In: 2nd International Conference and Workshop on Mathematical Analysis (ICWOMA 2016), 2-4 Aug. 2016, Langkawi, Malaysia. (pp. 1-8). 10.1063/1.4972168 |
| spellingShingle | Silalahi, Divo Dharma Midi, Habshah Considering a non-polynomial basis for local kernel regression problem |
| title | Considering a non-polynomial basis for local kernel regression problem |
| title_full | Considering a non-polynomial basis for local kernel regression problem |
| title_fullStr | Considering a non-polynomial basis for local kernel regression problem |
| title_full_unstemmed | Considering a non-polynomial basis for local kernel regression problem |
| title_short | Considering a non-polynomial basis for local kernel regression problem |
| title_sort | considering a non-polynomial basis for local kernel regression problem |
| url | http://psasir.upm.edu.my/id/eprint/57323/ 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 |