Package: baclava
Type: Package
Title: Bayesian Analysis of Cancer Latency with Auxiliary Variable
        Augmentation
Version: 1.1
Date: 2025-05-04
Authors@R: c(person("Raphael N.", "Morsomme",email = "raphael.morsomme@duke.edu", role = c("aut")), 
             person("Shannon T.", "Holloway",email = "shannon.t.holloway@gmail.com", role = c("aut", "cre")),
             person("Jason", "Xu",email = "jason.q.xu@duke.edu", role = c("ctb")),
             person("Marc D.", "Ryser", email = "marc.ryser@duke.edu", role = c("ctb")))
Description: A novel data-augmentation Markov chain Monte Carlo sampling algorithm to fit a progressive compartmental model of disease in a Bayesian framework 
             Morsomme, R.N., Holloway, S.T., Ryser, M.D. and Xu J. (2024) <doi:10.48550/arXiv.2408.14625>.
License: GPL-3
Depends: R (>= 4.1.0)
Imports: Rcpp, RcppNumerical, ggplot2, coda, dplyr, stats, tibble,
        tidyr, foreach, doParallel
LinkingTo: Rcpp, RcppEigen, RcppNumerical
Encoding: UTF-8
NeedsCompilation: yes
LazyData: true
Suggests: rmarkdown, knitr
Maintainer: Shannon T. Holloway <shannon.t.holloway@gmail.com>
Author: Raphael N. Morsomme [aut],
  Shannon T. Holloway [aut, cre],
  Jason Xu [ctb],
  Marc D. Ryser [ctb]
RoxygenNote: 7.3.2
Collate: 'RcppExports.R' 'aloocv.R' 'utilities.R' 'cohortODX.R'
        'computeEndpoints.R' 'fit_baclava.R' 'predictODX_helpers.R'
        'predictODX.R' 's3_methods.R' 'screen_data.R'
Packaged: 2025-05-04 17:02:28 UTC; sth45
Repository: CRAN
Date/Publication: 2025-05-04 17:20:02 UTC
Built: R 4.3.3; aarch64-apple-darwin20; 2025-05-04 17:55:31 UTC; unix
Archs: baclava.so.dSYM
