meshed: Bayesian Regression with Meshed Gaussian Processes

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>
License: GPL (≥ 3)
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: meshed results


Reference manual: meshed.pdf
Vignettes: MGPs for multivariate data at irregularly spaced locations
MGPs for univariate spatial gridded data
MGPs for univariate data at irregularly spaced locations
MGPs for univariate spatial non-Gaussian data


Package source: meshed_0.2.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): meshed_0.2.3.tgz, r-oldrel (arm64): meshed_0.2.3.tgz, r-release (x86_64): meshed_0.2.3.tgz, r-oldrel (x86_64): meshed_0.2.3.tgz
Old sources: meshed archive


Please use the canonical form to link to this page.