Package: bmetapred
Title: Bayesian Meta-Prediction in the Presence of Prediction Error
Version: 0.1.0
Authors@R: c(
    person("Jorge", "Piqueras Marqués", , "jorge.piqueras.m@gmail.com", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0002-6812-2106")),
    person("Anabel", "Forte Deltell", , "anabel.forte@uv.es", role = "aut",
           comment = c(ORCID = "0000-0001-9534-1817")),
    person("Joaquin", "Martinez Minaya", , "jmarmin@eio.upv.es", role = "ctb",
           comment = c(ORCID = "0000-0002-1016-8734"))
  )
Description: Fits pseudo-Bayesian Model Averaging (pBMA) and Bayesian Stacking ensembles of linear
    meta-models while explicitly accounting for the prediction errors of the individual models,
    building on the Bayesian Stacking of predictive distributions framework of Yao et al. (2018) <doi:10.1214/17-BA1091>.
    When native uncertainty estimates are unavailable, it provides tools to estimate heteroscedastic
    errors via Local Polynomial Regression (LOESS). The meta-model space is explored using exhaustive
    search, a Markov Chain Monte Carlo Model Composition (MC3) algorithm following Madigan and
    Raftery (1994) <doi:10.1080/01621459.1994.10476894> when pBMA is selected, or a tabu-guided heuristic search with parallel tempering when bayesian stacking is selected, all powered by 'brms' (Bürkner, 2017
    <doi:10.18637/jss.v080.i01>).
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 8.0.0
Imports: brms, future, future.apply, loo, stats, utils
NeedsCompilation: no
Packaged: 2026-10-19 12:51:46 UTC; General
Author: Jorge Piqueras Marqués [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-6812-2106>),
  Anabel Forte Deltell [aut] (ORCID:
    <https://orcid.org/0000-0001-9534-1817>),
  Joaquin Martinez Minaya [ctb] (ORCID:
    <https://orcid.org/0000-0002-1016-8734>)
Maintainer: Jorge Piqueras Marqués <jorge.piqueras.m@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-29 11:40:07 UTC
Built: R 4.5.2; ; 2026-10-29 14:59:04 UTC; unix
