Package: BayesNSGP
Title: Bayesian Analysis of Non-Stationary Gaussian Process Models
Description: Enables off-the-shelf functionality for fully Bayesian,
        nonstationary Gaussian process modeling. The approach to
        nonstationary modeling involves a closed-form,
        convolution-based covariance function with spatially-varying
        parameters; these parameter processes can be specified either
        deterministically (using covariates or basis functions) or
        stochastically (using approximate Gaussian processes).
        Stationary Gaussian processes are a special case of our
        methodology, and we furthermore implement approximate Gaussian
        process inference to account for very large spatial data sets
        (Finley, et al (2017) <doi:10.48550/arXiv.1702.00434>).
        Bayesian inference is carried out using Markov chain Monte
        Carlo methods via the "nimble" package, and posterior
        prediction for the Gaussian process at unobserved locations is
        provided as a post-processing step. Also provided are
        nearest-neighbor Gaussian process components for use directly
        in user-written model code, where the spatial process is
        retained as a latent field: neighbor-structure construction, a
        latent-field density and matching simulation function, a
        purpose-built Metropolis-Hastings sampler that updates the
        field one node at a time, and posterior prediction at
        unobserved locations.
Version: 0.3.1
Date: 2026-09-10
Maintainer: Daniel Turek <danielturek@gmail.com>
Authors@R: c(person("Daniel", "Turek",    role = c("aut", "cre"), email = "danielturek@gmail.com"),
             person("Mark", "Risser",     role = "aut"),
             person("Fabian", "Ketwaroo", role = "aut"))
Depends: R (>= 3.4.0),nimble
Imports: FNN,Matrix,methods,StatMatch,sf,ggplot2
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
License: GPL-3
Encoding: UTF-8
Config/roxygen2/version: 8.1.0
RoxygenNote: 7.3.2
NeedsCompilation: no
Packaged: 2026-10-11 15:26:35 UTC; root
Author: Daniel Turek [aut, cre], Mark Risser [aut], Fabian Ketwaroo
        [aut]
Config/pak/sysreqs: libabsl-dev cmake libgdal-dev gdal-bin libgeos-dev
        libglpk-dev make libxml2-dev libssl-dev libproj-dev
        libsqlite3-dev libudunits2-dev
Repository: https://danielturek.r-universe.dev
Date/Publication: 2026-09-10 14:31:03 UTC
RemoteUrl: https://github.com/cran/BayesNSGP
RemoteRef: HEAD
RemoteSha: 7d166335eb8919f2151de05e0422ba6d0c899d6c