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Splines as a Useful and Convenient Statistical Tool
Abstract
The framework for a unified statistical theory of spline regression assuming fixed knots using the truncated polynomial or “+” function representation is presented. In particular, a partial ordering of some spline models is introduced to clarify their relationship and to indicate the hypotheses that can be tested by using either standard multiple regression procedures or a little-used conditional test developed by Hotelling (1940). The construction of spline models with polynomial pieces of different degrees is illustrated. A numerical example from a chemical experiment is given by using the GLM procedure of the statistical software package SAS (Barr et al. 1976).
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Cited by
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Silverman, B. W. (1985) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1985.tb01327.x · Cited by 1,117
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Weiser, T. G., Haynes, A. B., Molina, G., Lipsitz, S. R., Esquivel, M. M., Uribe-Leitz, T., Fu, R., Azad, T., Chao, T. E., Berry, W. R., et al. (2016) · Bulletin of the World Health Organization · doi:10.2471/blt.15.159293 · Cited by 655
Metadata
- Authors
- Smith, P. L.
- Venue
- The American Statistician
- Publisher
- Informa UK Limited
- Published
- 1979-05
- Volume
- 33
- Issue
- 2
- Pages
- 57-62
- ISSN
- 0003-1305 (ISSN-L)
- 1537-2731
- OpenAlex
- W4237622357
- Cited by
- 422
- References
- 0
- FWCI
- 5.84
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
