Package: matrixCorr
Type: Package
Title: Collection of Correlation and Association Estimators
Version: 0.6.2
Authors@R: person(given = "Thiago de Paula", family = "Oliveira", 
    email = "thiago.paula.oliveira@gmail.com", role = c("aut", "cre"), 
    comment = c(ORCID = "0000-0002-4555-2584"))
Description: Compute correlation and other association matrices from
    small to high-dimensional datasets with relative simple functions and
    sensible defaults. Includes options for shrinkage and robustness to improve
    results in noisy or high-dimensional settings (p >= n), plus convenient
    print/plot methods for inspection. Implemented with optimised C++ backends
    using BLAS/OpenMP and memory-aware symmetric updates. Works with base
    matrices and data frames, returning standard R objects via a consistent S3
    interface. Useful across genomics, agriculture, and machine-learning
    workflows. Supports Pearson, Spearman, Kendall, distance correlation,
    partial correlation, and robust biweight mid-correlation; Bland–Altman
    analyses and Lin's concordance correlation coefficient (including
    repeated-measures extensions). Methods based on Ledoit and Wolf (2004)
    <doi:10.1016/S0047-259X(03)00096-4>; Schäfer and Strimmer (2005)
    <doi:10.2202/1544-6115.1175>; Lin (1989) <doi:10.2307/2532051>.
License: MIT + file LICENSE
Encoding: UTF-8
LinkingTo: cpp11, Rcpp, RcppArmadillo
Imports: Rcpp (>= 1.1.0), ggplot2 (>= 3.5.2), Matrix (>= 1.7.2)
Suggests: knitr, rmarkdown, testthat, MASS, viridisLite
RoxygenNote: 7.3.3
URL: https://github.com/Prof-ThiagoOliveira/matrixCorr
BugReports: https://github.com/Prof-ThiagoOliveira/matrixCorr/issues
NeedsCompilation: yes
Packaged: 2025-11-15 07:57:31 UTC; ThiagoOliveira
Author: Thiago de Paula Oliveira [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-4555-2584>)
Maintainer: Thiago de Paula Oliveira <thiago.paula.oliveira@gmail.com>
Repository: CRAN
Date/Publication: 2025-11-15 11:50:11 UTC
Built: R 4.5.2; x86_64-w64-mingw32; 2025-11-15 12:36:04 UTC; windows
Archs: x64
