print.summary.matrixCorr

Prints compact summary statistics returned by matrix-style
<code><a href="/link/summary()?package=matrixCorr&version=0.12.3" data-mini-rdoc="matrixCorr::summary()">summary()</a></code> methods in matrixCorr.

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 >= 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, including robust
concordance based on minimum covariance determinant estimates.
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) <doi:10.1016/S0047-259X(03)00096-4>;
high-dimensional shrinkage covariance estimation
<doi:10.2202/1544-6115.1175>; Lin (1989) <doi:10.2307/2532051>; Wilcox
(1994) <doi:10.1007/BF02294395>; Wilcox (2004)
<doi:10.1080/0266476032000148821>; Hayes and Krippendorff (2007)
<doi:10.1080/19312450709336664>; weighted repeated-measures correlation by
Kondo et al. (2025) <doi:10.1002/sim.70046>.

Thiago de Paula Oliveira

matrixCorr

Collection of Correlation, Agreement, and Reliability Estimators

print.summary.matrixCorr function

<dl><dt>x</dt>
<dd>An object of class <code>summary.matrixCorr</code>.</dd>
<dt>digits</dt>
<dd>Integer; number of decimal places to print.</dd>
<dt>n</dt>
<dd>Optional row threshold for compact preview output.</dd>
<dt>topn</dt>
<dd>Optional number of leading/trailing rows to show when truncated.</dd>
<dt>max_vars</dt>
<dd>Optional maximum number of visible columns; <code>NULL</code> derives this
from console width.</dd>
<dt>width</dt>
<dd>Optional display width; defaults to <code>getOption("width")</code>.</dd>
<dt>show_ci</dt>
<dd>One of <code>"yes"</code> or <code>"no"</code>.</dd>
<dt>...</dt>
<dd>Unused.</dd></dl>

Arguments

Prints compact summary statistics returned by matrix-style
<code><a href='https://rdrr.io/r/base/summary.html'>summary()</a></code> methods in matrixCorr.

Summary Method for Correlation Matrices — print.summary.matrixCorr

<dl>

<dt>x</dt>
<dd>An object of class <code>summary.matrixCorr</code>.</dd>


<dt>digits</dt>
<dd>Integer; number of decimal places to print.</dd>


<dt>n</dt>
<dd>Optional row threshold for compact preview output.</dd>


<dt>topn</dt>
<dd>Optional number of leading/trailing rows to show when truncated.</dd>


<dt>max_vars</dt>
<dd>Optional maximum number of visible columns; <code>NULL</code> derives this
from console width.</dd>


<dt>width</dt>
<dd>Optional display width; defaults to <code>getOption("width")</code>.</dd>


<dt>show_ci</dt>
<dd>One of <code>"yes"</code> or <code>"no"</code>.</dd>


<dt>...</dt>
<dd>Unused.</dd>

</dl>

print.summary.matrixCorr: Summary Method for Correlation Matrices

Description

Usage

Value

Arguments