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<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Collection of Correlation, Agreement, and Reliability Estimators</dc:title>
  <dc:title>R package matrixCorr version 0.12.2</dc:title>
  <dc:description>Compute correlation, association, agreement, and reliability
    measures for small to high-dimensional datasets through a consistent
    matrix-oriented interface. Supports classical correlations (Pearson,
    Spearman, Kendall, Chatterjee's rank correlation), distance correlation, partial correlation with
    regularised estimators, shrinkage correlation for p &gt;= n settings, robust
    correlations including biweight mid-correlation, percentage-bend,
    Winsorized, and skipped correlation, latent-variable methods for binary
    and ordinal data, pairwise and overall intraclass correlation for wide
    data, repeated-measures correlation, and agreement/reliability analyses
    based on Cohen's kappa, weighted kappa, multi-rater kappa, Gwet's AC1/AC2,
    Krippendorff's alpha, Bland-Altman methods, Lin's concordance correlation
    coefficient, Poisson GLMM concordance for count data, and
    repeated-measures intraclass/concordance correlation.
    Implemented with optimized C++ backends using BLAS/OpenMP and memory-aware
    symmetric updates, and returns standard R objects with print/summary/plot
    methods plus optional Shiny viewers for matrix inspection. Methods based
    on Ledoit and Wolf (2004) &lt;doi:10.1016/S0047-259X(03)00096-4&gt;;
    high-dimensional shrinkage covariance estimation
    &lt;doi:10.2202/1544-6115.1175&gt;; Lin (1989) &lt;doi:10.2307/2532051&gt;; Wilcox
    (1994) &lt;doi:10.1007/BF02294395&gt;; Wilcox (2004)
    &lt;doi:10.1080/0266476032000148821&gt;; Hayes and Krippendorff (2007)
    &lt;doi:10.1080/19312450709336664&gt;; weighted repeated-measures correlation by
    Kondo et al. (2025) &lt;doi:10.1002/sim.70046&gt;.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.4.0)</dc:relation>
  <dc:relation>Imports: Rcpp (&gt;= 1.1.0), ggplot2 (&gt;= 3.5.2), Matrix (&gt;= 1.7.2), cli,
generics, rlang</dc:relation>
  <dc:relation>LinkingTo: Rcpp, RcppArmadillo</dc:relation>
  <dc:relation>Suggests: knitr, rmarkdown, MASS, mnormt, shiny, shinyWidgets,
viridisLite, testthat (&gt;= 3.0.0)</dc:relation>
  <dc:relation>Enhances: plotly</dc:relation>
  <dc:creator>Thiago de Paula Oliveira &lt;thiago.paula.oliveira@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Thiago de Paula Oliveira [aut, cre] (ORCID:
    &lt;https://orcid.org/0000-0002-4555-2584&gt;)</dc:contributor>
  <dc:rights>GPL (&gt;= 3)</dc:rights>
  <dc:date>2026-05-31</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=matrixCorr</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.matrixCorr</dc:identifier>
</oai_dc:dc>
