The DOI matches its Crossref record.
Non-Parametric Function Fitting
Abstract
Summary: In this note we consider the problem of fitting a general functional relationship between two variables. We require only that the function to be fitted is, in some sense, “smooth”, and do not assume that it has a known mathematical form involving only a finite number of unknown parameters.
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Citations
Cited by
Some aspects of the spline smoothing approach to non-parametric regression curve fitting
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
Kernel Smoothing in Partial Linear Models
Speckman, P. (1988) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1988.tb01738.x · Cited by 986
Metadata
- Authors
- Priestley, M. B., & Chao, M. T.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 1972-07-01
- Volume
- 34
- Issue
- 3
- Pages
- 385-392
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W2560458561
- Cited by
- 467
- References
- 0
- FWCI
- 1.95
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
