Smoothing Errors
The problem of obtaining an error assessment for smoothing splines is investigated. Depending on different modeling assumptions like the Bayesian, minimax or signal extraction approach which is related to kriging and cokriging. smoothing errors can be derived. The resulting smoothing errors are show...
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| Veröffentlicht in: | Statistics (Berlin, DDR) DDR), 1998-01, Vol.31 (2), p.91-114 |
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| container_end_page | 114 |
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| container_issue | 2 |
| container_start_page | 91 |
| container_title | Statistics (Berlin, DDR) |
| container_volume | 31 |
| creator | Van Der Linde, Angelika |
| description | The problem of obtaining an error assessment for smoothing splines is investigated. Depending on different modeling assumptions like the Bayesian, minimax or signal extraction approach which is related to kriging and cokriging. smoothing errors can be derived. The resulting smoothing errors are shown to be coincident. |
| doi_str_mv | 10.1080/02331889808802631 |
| format | Article |
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| fulltext | fulltext |
| identifier | ISSN: 0233-1888 |
| ispartof | Statistics (Berlin, DDR), 1998-01, Vol.31 (2), p.91-114 |
| issn | 0233-1888 1029-4910 |
| language | eng |
| recordid | cdi_crossref_primary_10_1080_02331889808802631 |
| source | Taylor & Francis:Master (3349 titles) |
| subjects | kriging Smoothing splines |
| title | Smoothing Errors |
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