DESCRIPTION

Package: designbgm
Date: 2026-08-11  
Type: Package
Title: Sample Size Planning for Bayesian Graphical Models
Version: 0.3.0
Authors@R: c(person(given = "Giuseppe",
             family = "Arena",
             role = c("aut", "cre"),
             email = "g.arena@uva.nl",
             comment = c(ORCID = "0000-0001-5204-3326")))
Maintainer: Giuseppe Arena <g.arena@uva.nl>
Description: Plans sample sizes of a prospective study for a Bayesian graphical model, given a prior elicited from a previous study. Three planning methods are available: a data-to-prior information ratio over the model parameters, Bayes factor design analysis at a representative edge, and a structural design analysis targeting whole-network sensitivity or specificity. Estimators of the prior effective sample size quantify how much information the elicited prior carries, and planned sample sizes can be validated by simulation. Gaussian graphical models are currently supported.
License: MIT + file LICENSE
URL: https://bayesian-graphical-modelling-lab.github.io/designbgm/
BugReports: https://github.com/Bayesian-Graphical-Modelling-Lab/designbgm/issues
Depends:
    R (>= 4.4.0)
Imports:
    stats,
    igraph,
    Rcpp (>= 1.1.0)
Suggests:
    knitr,
    rmarkdown,
    tinytest,
    huge,
    qgraph,
    bootnet
LinkingTo:
    Rcpp,
    RcppArmadillo
SystemRequirements: OpenMP
VignetteBuilder:
    knitr
Encoding: UTF-8
Language: en-US
RoxygenNote: 7.3.3