DESCRIPTION

Package: multilevelcoda
Type: Package
Title: Estimate Bayesian Multilevel Models for Compositional Data
Version: 1.3.1
Date: 2024-11-11
Authors@R: 
    c(person(given = "Flora",
             family = "Le",
             role = c("aut", "cre"),
             email = "floralebui@gmail.com",
             comment = c(ORCID = "0000-0003-0089-8167")),
      person(given = "Joshua F.",
             family = "Wiley",
             role = c("aut"),
             email = "jwiley.psych@gmail.com",
             comment = c(ORCID = "0000-0002-0271-6702")))
URL: https://florale.github.io/multilevelcoda/,
     https://github.com/florale/multilevelcoda
BugReports: https://github.com/florale/multilevelcoda/issues
Description: Implement Bayesian Multilevel Modelling for compositional data 
             in a multilevel framework. Compute multilevel compositional data and 
             Isometric log ratio (ILR) at between and within-person levels, 
             fit Bayesian multilevel models for compositional predictors and outcomes, 
             and run post-hoc analyses such as isotemporal substitution models.
             References: 
             Le, Stanford, Dumuid, and Wiley (2024) <doi:10.48550/arXiv.2405.03985>,
             Le, Dumuid, Stanford, and Wiley (2024) <doi:10.48550/arXiv.2411.12407>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Depends:
    R (>= 4.0.0)
Imports: 
    stats,
    data.table (>= 1.12.0),
    compositions,
    brms,
    bayestestR,
    extraoperators,
    ggplot2,
    foreach,
    future,
    doFuture,
    abind,
    graphics,
    shiny,
    shinystan,
    plotly,
    hrbrthemes,
    bslib,
    DT,
    loo,
    bayesplot,
    emmeans,
    posterior
Suggests: 
    testthat (>= 3.0.0),
    covr,
    withr,
    knitr,
    rmarkdown,
    lme4,
    cmdstanr (>= 0.5.0)
Config/testthat/edition: 3
Config/testthat/parallel: true
Additional_repositories: 
    https://mc-stan.org/r-packages/
VignetteBuilder: knitr