Bayesian projection pursuit regression-Reference-Cited by-同舟云学术

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Bayesian projection pursuit regression

Published:2023-11-04 Issue:1 Volume:34 Page:
ISSN:0960-3174
Container-title:Statistics and Computing
language:en
Short-container-title:Stat Comput

Author:

Collins Gavin,Francom Devin,Rumsey Kellin

Funder

Los Alamos National Laboratory

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Statistics, Probability and Uncertainty,Statistics and Probability,Theoretical Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s11222-023-10334-z.pdf

Reference45 articles.

1. Antoniadis, A., Grégoire, G., McKeague, I.W.: Bayesian estimation in single-index models. Stat. Sin. 14(4), 1147–1164 (2004)

2. Apley, D.W., Jingyu, Z.: Visualizing the effects of predictor variables in black box supervised learning models. J. R. Stat. Soc.: Ser. B (Statistical Methodology) 82(4), 1059–1086 (2020). https://doi.org/10.1111/rssb.12377

3. Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001). https://doi.org/10.1023/A:1010933404324

4. Brillinger, D.R.: The identification of a particular nonlinear time series system. Biometrika 64(3), 509–515 (1977). https://doi.org/10.2307/2345326

5. Brillinger, D.R.: A generalized linear model with “gaussian’’ regressor variables. In: Guttorp, P., Brillinger, D. (eds.) Selected Works of David Brillinger. Selected Works in Probability and Statistics., pp. 589–606. Springer, New York (2012)

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2. Discovering Active Subspaces for High-Dimensional Computer Models;Journal of Computational and Graphical Statistics;2023-11-03

3. A localized ensemble of approximate Gaussian processes for fast sequential emulation;Stat;2023-01

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