DESCRIPTION

Package: jlmerclusterperm
Title: Cluster-Based Permutation Analysis for Densely Sampled Time Data
Version: 1.1.4
Authors@R: 
    person("June", "Choe", , "jchoe001@gmail.com", role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0002-0701-921X"))
Description: An implementation of fast cluster-based permutation analysis
    (CPA) for densely-sampled time data developed in Maris & Oostenveld,
    2007 <doi:10.1016/j.jneumeth.2007.03.024>. Supports (generalized,
    mixed-effects) regression models for the calculation of timewise
    statistics. Provides both a wholesale and a piecemeal interface to the
    CPA procedure with an emphasis on interpretability and diagnostics.
    Integrates 'Julia' libraries 'MixedModels.jl' and 'GLM.jl' for
    performance improvements, with additional functionalities for
    interfacing with 'Julia' from 'R' powered by the 'JuliaConnectoR'
    package.
License: MIT + file LICENSE
URL: https://github.com/yjunechoe/jlmerclusterperm,
    https://yjunechoe.github.io/jlmerclusterperm/
BugReports: https://github.com/yjunechoe/jlmerclusterperm/issues
Depends:
    R (>= 3.5)
Imports: 
    backports (>= 1.1.7),
    cli,
    generics,
    JuliaConnectoR,
    JuliaFormulae,
    lme4,
    stats,
    tools,
    utils
Suggests:
    broom,
    broom.mixed,
    covr,
    dplyr,
    eyetrackingR,
    forcats,
    future,
    ggplot2,
    knitr,
    MASS,
    patchwork,
    readr,
    rmarkdown,
    scales,
    testthat (>= 3.0.0),
    tibble
VignetteBuilder: 
    knitr
Config/testthat/edition: 3
Encoding: UTF-8
Roxygen: list(markdown = TRUE, roclets = c ("namespace", "rd",
    "srr::srr_stats_roclet"))
RoxygenNote: 7.3.2
SystemRequirements: Julia (>= 1.8)
Collate:
    'jlmerclusterperm-package.R'
    'aaa.R'
    'utils.R'
    'interop-utils.R'
    'interop-utils-unexported.R'
    'julia_rng.R'
    'jlmer_spec.R'
    'jlmer.R'
    'compute_timewise_statistics.R'
    'permute.R'
    'permute_timewise_statistics.R'
    'clusters_methods.R'
    'extract_clusters.R'
    'calculate_pvalue.R'
    'clusterpermute.R'
    'threshold_search.R'
    'tidy.R'
    'zzz.R'
    'srr-stats-standards.R'