Package: womblR
Type: Package
Title: Spatiotemporal Boundary Detection Model for Areal Unit Data
Version: 1.0.6
Description: Implements a spatiotemporal boundary detection model with
        a dissimilarity metric for areal data with inference in a
        Bayesian setting using Markov chain Monte Carlo (MCMC). The
        response variable can be modeled as Gaussian (no nugget),
        probit or Tobit link and spatial correlation is introduced at
        each time point through a conditional autoregressive (CAR)
        prior. Temporal correlation is introduced through a
        hierarchical structure and can be specified as exponential or
        first-order autoregressive. Full details of the package can be
        found in the accompanying vignette. Furthermore, the details of
        the package can be found in "Diagnosing Glaucoma Progression
        with Visual Field Data Using a Spatiotemporal Boundary
        Detection Method", by Berchuck et al (2019)
        <doi:10.1080/01621459.2018.1537911>.
Date: 2025-09-26
Authors@R: person("Samuel I.", "Berchuck", email = "sib2@duke.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5705-3144"))
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.2
NeedsCompilation: yes
Depends: R (>= 3.0.2)
Imports: graphics, grDevices, msm (>= 1.0.0), mvtnorm (>= 1.0-0), Rcpp
        (>= 0.12.9), stats, utils
Suggests: coda, classInt, knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo (>= 0.7.500.0.0)
VignetteBuilder: knitr
Repository: https://berchuck.r-universe.dev
Date/Publication: 2025-09-29 17:03:52 UTC
RemoteUrl: https://github.com/berchuck/womblr
RemoteRef: HEAD
RemoteSha: d77aed54ba9228cfe5113da2ca3c70747d8b6a74
Packaged: 2026-06-24 12:11:20 UTC; root
Author: Samuel I. Berchuck [aut, cre] (ORCID:
    <https://orcid.org/0000-0001-5705-3144>)
Maintainer: Samuel I. Berchuck <sib2@duke.edu>