print.matrixCorr_ccc_ci

Print method for matrixCorr CCC objects with CIs

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>.

Thiago de Paula Oliveira

matrixCorr

Collection of Correlation and Association Estimators

print.matrixCorr_ccc_ci function

<dl><dt>x</dt>
<dd>A <code>matrixCorr_ccc</code> or <code>matrixCorr_ccc_ci</code> object.</dd>
<dt>...</dt>
<dd>Passed to underlying printers.</dd></dl>

Arguments

Print method for matrixCorr CCC objects with CIs — print.matrixCorr_ccc_ci

<dl>

<dt>x</dt>
<dd>A <code>matrixCorr_ccc</code> or <code>matrixCorr_ccc_ci</code> object.</dd>


<dt>...</dt>
<dd>Passed to underlying printers.</dd>

</dl>

print.matrixCorr_ccc_ci: Print method for matrixCorr CCC objects with CIs

Description

Usage

Arguments