Package: BayesGP
Type: Package
Title: Efficient Implementation of Gaussian Process in Bayesian
        Hierarchical Models
Version: 0.1.3
Authors@R: c(person(given = "Ziang",
                        family = "Zhang",
                        role = c("aut", "cre"),
                        email = "ziangzhang@uchicago.edu"),
                 person(given = "Yongwei",
                        family = "Lin",
                        role = "aut"),
                 person(given = "Alex",
                        family = "Stringer",
                        role = "aut"),
                 person(given = "Patrick",
                        family = "Brown",
                        role = "aut"))
Description: Implements Bayesian hierarchical models with flexible Gaussian process priors, focusing on Extended Latent Gaussian Models and incorporating various Gaussian process priors for Bayesian smoothing. Computations leverage finite element approximations and adaptive quadrature for efficient inference. Methods are detailed in Zhang, Stringer, Brown, and Stafford (2023) <doi:10.1177/09622802221134172>; Zhang, Stringer, Brown, and Stafford (2024) <doi:10.1080/10618600.2023.2289532>; Zhang, Brown, and Stafford (2023) <doi:10.48550/arXiv.2305.09914>; and Stringer, Brown, and Stafford (2021) <doi:10.1111/biom.13329>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2
LinkingTo: TMB (>= 1.9.7), RcppEigen
Imports: TMB (>= 1.9.7), numDeriv, rstan, sfsmisc, Matrix (>= 1.6.3),
        aghq (>= 0.4.1), fda, tmbstan, LaplacesDemon, methods
Depends: R (>= 3.6.0)
Suggests: rmarkdown, knitr, survival, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2024-11-10 22:31:24 UTC; ziangzhang
Config/testthat/edition: 3
Author: Ziang Zhang [aut, cre],
  Yongwei Lin [aut],
  Alex Stringer [aut],
  Patrick Brown [aut]
Maintainer: Ziang Zhang <ziangzhang@uchicago.edu>
Repository: CRAN
Date/Publication: 2024-11-12 14:20:03 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-30 07:36:52 UTC; unix
Archs: BayesGP.so.dSYM
