Package: spDBL
Title: Dynamic Bayesian Learning for Spatiotemporal Mechanistic Models
Version: 1.0.2
Authors@R: c(
    person("Xiang", "Chen", email = "xiangchen@ucla.edu", role = c("aut", "cre")),
    person("Sudipto", "Banerjee", email = "sudipto@ucla.edu", role = c("aut"))
  )
Description: Provides tools for Bayesian learning of spatiotemporal
        dynamical mechanistic models. Includes methods for parameter
        estimation, simulation, and inference using hierarchical and
        state-space modeling approaches, following Banerjee, Chen,
        Frankenburg and Zhou (2025)
        <https://jmlr.org/papers/v26/22-0896.html>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0)
RoxygenNote: 7.3.3
LinkingTo: Rcpp, RcppEigen
Imports: Rcpp, matrixsampling, invgamma, deSolve, ReacTran,
        LaplacesDemon, matrixcalc, mniw, utils, stats, ggpubr, ggplot2,
        readr, magrittr, rlang, scales
Suggests: testthat (>= 3.0.0), here, knitr, rmarkdown
Config/testthat/edition: 3
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2026-09-27 09:57:09 UTC; root
Author: Xiang Chen [aut, cre], Sudipto Banerjee [aut]
Maintainer: Xiang Chen <xiangchen@ucla.edu>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-06-09 08:44:41 UTC
RemoteUrl: https://github.com/cran/spDBL
RemoteRef: HEAD
RemoteSha: ce91035c804b0c25514ecc18212184d23b5d285b