doi:10.1080/01621459.2020.1833889>, Peruzzi, Banerjee, Dunson, and Finley (2021) <doi:10.48550/arXiv.2101.03579>, Peruzzi and Dunson (2022) <doi:10.48550/arXiv.2201.10080>. Funded by ERC grant 856506 and NIH grant R01ES028804.">

meshed: Bayesian Regression with Meshed Gaussian Processes (original) (raw)

Fits Bayesian regression models based on latent Meshed Gaussian Processes (MGP) as described in Peruzzi, Banerjee, Finley (2020) <doi:10.1080/01621459.2020.1833889>, Peruzzi, Banerjee, Dunson, and Finley (2021) <doi:10.48550/arXiv.2101.03579>, Peruzzi and Dunson (2022) <doi:10.48550/arXiv.2201.10080>. Funded by ERC grant 856506 and NIH grant R01ES028804.

Version: 0.2.3
Imports: Rcpp (≥ 1.0.5), stats, dplyr, glue, rlang, magrittr, FNN
LinkingTo: Rcpp, RcppArmadillo
Suggests: ggplot2, abind, rmarkdown, knitr, tidyr
Published: 2022-09-19
DOI: 10.32614/CRAN.package.meshed
Author: Michele Peruzzi
Maintainer: Michele Peruzzi <michele.peruzzi at duke.edu>
License: GPL (≥ 3)
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: meshed results

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