
Bayesian local extremum splines
Publication
, Journal Article
Wheeler, MW; Dunson, DB; Herring, AH
Published in: Biometrika
December 1, 2017
We consider shape-restricted nonparametric regression on a closed set $$\mathcal{X} \subset \mathbb{R},$$ where it is reasonable to assume that the function has no more than $$H$$ local extrema interior to $$\mathcal{X}$$. Following a Bayesian approach we develop a nonparametric prior over a novel class of local extremum splines. This approach is shown to be consistent when modelling any continuously differentiable function within the class considered, and we use itto develop methods for testing hypotheses on the shape of the curve. Sampling algorithms are developed, and the method is applied in simulation studies and data examples where the shape of the curve is of interest.
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Published In
Biometrika
DOI
ISSN
0006-3444
Publication Date
December 1, 2017
Volume
104
Issue
4
Start / End Page
939 / 952
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1403 Econometrics
- 0104 Statistics
- 0103 Numerical and Computational Mathematics
Citation
APA
Chicago
ICMJE
MLA
NLM
Wheeler, M. W., Dunson, D. B., & Herring, A. H. (2017). Bayesian local extremum splines. Biometrika, 104(4), 939–952. https://doi.org/10.1093/biomet/asx039
Wheeler, M. W., D. B. Dunson, and A. H. Herring. “Bayesian local extremum splines.” Biometrika 104, no. 4 (December 1, 2017): 939–52. https://doi.org/10.1093/biomet/asx039.
Wheeler MW, Dunson DB, Herring AH. Bayesian local extremum splines. Biometrika. 2017 Dec 1;104(4):939–52.
Wheeler, M. W., et al. “Bayesian local extremum splines.” Biometrika, vol. 104, no. 4, Dec. 2017, pp. 939–52. Manual, doi:10.1093/biomet/asx039.
Wheeler MW, Dunson DB, Herring AH. Bayesian local extremum splines. Biometrika. 2017 Dec 1;104(4):939–952.

Published In
Biometrika
DOI
ISSN
0006-3444
Publication Date
December 1, 2017
Volume
104
Issue
4
Start / End Page
939 / 952
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1403 Econometrics
- 0104 Statistics
- 0103 Numerical and Computational Mathematics