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meshed

Bayesian Regression with Meshed Gaussian Processes

Installation

About

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) , Peruzzi and Dunson (2022) . Funded by ERC grant 856506 and NIH grant R01ES028804.

Key Metrics

Version 0.2.3
Published 2022-09-19 587 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks meshed results

Downloads

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Maintainer

Maintainer

Michele Peruzzi

michele.peruzzi@duke.edu

Authors

Michele Peruzzi

Material

README
NEWS
Reference manual
Package source

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

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

meshed archive

Imports

Rcpp ≥ 1.0.5
stats
dplyr
glue
rlang
magrittr
FNN

Suggests

ggplot2
abind
rmarkdown
knitr
tidyr

LinkingTo

Rcpp
RcppArmadillo