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: 2026-06-04 01:55:41 UTC; xiangchen
Author: Xiang Chen [aut, cre],
  Sudipto Banerjee [aut]
Maintainer: Xiang Chen <xiangchen@ucla.edu>
Repository: CRAN
Date/Publication: 2026-06-09 07:20:02 UTC
Built: R 4.4.3; x86_64-apple-darwin20; 2026-06-09 09:12:29 UTC; unix
Archs: spDBL.so.dSYM
