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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 |
| Package source: | meshed_0.2.3.tar.gz |
| Windows binaries: | r-devel: meshed_0.2.3.zip, r-release: meshed_0.2.3.zip, r-oldrel: meshed_0.2.3.zip |
| 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 |
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These binaries (installable software) and packages are in development.
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