V-Splines and Bayes Estimate
Smoothing splines can be thought of as the posterior mean of a Gaussian process regression in a certain limit. By constructing a reproducing kernel Hilbert space with an appropriate inner product, the Bayesian form of the V-spline is derived when the penalty term is a fixed constant instead of a...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/78085 |
| _version_ | 1848763931506507776 |
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| author | Cao, Zhanglong Bryant, David Parry, Matthew |
| author_facet | Cao, Zhanglong Bryant, David Parry, Matthew |
| author_sort | Cao, Zhanglong |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Smoothing splines can be thought of as the posterior mean of a Gaussian
process regression in a certain limit. By constructing a reproducing kernel
Hilbert space with an appropriate inner product, the Bayesian form of the
V-spline is derived when the penalty term is a fixed constant instead of a
function. An extension to the usual generalized cross-validation formula is
utilized to find the optimal V-spline parameters. |
| first_indexed | 2025-11-14T11:11:18Z |
| format | Journal Article |
| id | curtin-20.500.11937-78085 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:11:18Z |
| publishDate | 2018 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-780852020-09-01T05:02:27Z V-Splines and Bayes Estimate Cao, Zhanglong Bryant, David Parry, Matthew math.ST math.ST stat.TH Smoothing splines can be thought of as the posterior mean of a Gaussian process regression in a certain limit. By constructing a reproducing kernel Hilbert space with an appropriate inner product, the Bayesian form of the V-spline is derived when the penalty term is a fixed constant instead of a function. An extension to the usual generalized cross-validation formula is utilized to find the optimal V-spline parameters. 2018 Journal Article http://hdl.handle.net/20.500.11937/78085 restricted |
| spellingShingle | math.ST math.ST stat.TH Cao, Zhanglong Bryant, David Parry, Matthew V-Splines and Bayes Estimate |
| title | V-Splines and Bayes Estimate |
| title_full | V-Splines and Bayes Estimate |
| title_fullStr | V-Splines and Bayes Estimate |
| title_full_unstemmed | V-Splines and Bayes Estimate |
| title_short | V-Splines and Bayes Estimate |
| title_sort | v-splines and bayes estimate |
| topic | math.ST math.ST stat.TH |
| url | http://hdl.handle.net/20.500.11937/78085 |