| 000 | 02291nam a2200349 i 4500 | ||
|---|---|---|---|
| 001 | CR9781108610247 | ||
| 003 | UkCbUP | ||
| 005 | 20240916171948.0 | ||
| 006 | m|||||o||d|||||||| | ||
| 007 | cr|||||||||||| | ||
| 008 | 180628s2021||||enk o ||1 0|eng|d | ||
| 020 | _a9781108610247 (ebook) | ||
| 020 | _z9781108482950 (hardback) | ||
| 040 |
_aUkCbUP _beng _erda _cUkCbUP |
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| 050 | 0 | 0 |
_aQA278 _b.E397 2021 |
| 082 | 0 | 0 |
_a511/.4223 _223 |
| 100 | 1 |
_aEilers, Paul H. C., _d1948- _eauthor. |
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| 245 | 1 | 0 |
_aPractical smoothing : _bthe joys of P-splines / _cPaul H.C. Eilers, Brian D. Marx. |
| 264 | 1 |
_aCambridge : _bCambridge University Press, _c2021. |
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| 300 |
_a1 online resource (xii, 199 pages) : _bdigital, PDF file(s). |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 500 | _aTitle from publisher's bibliographic system (viewed on 26 Feb 2021). | ||
| 520 | _aThis is a practical guide to P-splines, a simple, flexible and powerful tool for smoothing. P-splines combine regression on B-splines with simple, discrete, roughness penalties. They were introduced by the authors in 1996 and have been used in many diverse applications. The regression basis makes it straightforward to handle non-normal data, like in generalized linear models. The authors demonstrate optimal smoothing, using mixed model technology and Bayesian estimation, in addition to classical tools like cross-validation and AIC, covering theory and applications with code in R. Going far beyond simple smoothing, they also show how to use P-splines for regression on signals, varying-coefficient models, quantile and expectile smoothing, and composite links for grouped data. Penalties are the crucial elements of P-splines; with proper modifications they can handle periodic and circular data as well as shape constraints. Combining penalties with tensor products of B-splines extends these attractive properties to multiple dimensions. An appendix offers a systematic comparison to other smoothers. | ||
| 650 | 0 | _aSmoothing (Statistics) | |
| 650 | 0 | _aSpline theory. | |
| 700 | 1 |
_aMarx, Brian D., _d1960- _eauthor. |
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| 776 | 0 | 8 |
_iPrint version: _z9781108482950 |
| 856 | 4 | 0 | _uhttps://doi.org/10.1017/9781108610247 |
| 942 |
_2ddc _cEB |
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| 999 |
_c9888 _d9888 |
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