# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "bmetapred" in publications use:' type: software license: GPL-3.0-or-later title: 'bmetapred: Bayesian Meta-Prediction in the Presence of Prediction Error' version: 0.1.0 doi: 10.32614/CRAN.package.bmetapred abstract: 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) . 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) when pBMA is selected, or a tabu-guided heuristic search with parallel tempering when bayesian stacking is selected, all powered by 'brms' (Bürkner, 2017 ). authors: - family-names: Piqueras Marqués given-names: Jorge email: jorge.piqueras.m@gmail.com orcid: https://orcid.org/0000-0002-6812-2106 - family-names: Forte Deltell given-names: Anabel email: anabel.forte@uv.es orcid: https://orcid.org/0000-0001-9534-1817 repository: https://jorgepiquerasmarques.r-universe.dev commit: 05e6001147cedc3fcaccd679c20f986082c1cf6e date-released: '2026-10-29' contact: - family-names: Piqueras Marqués given-names: Jorge email: jorge.piqueras.m@gmail.com orcid: https://orcid.org/0000-0002-6812-2106