matrixCorr-internal

validate_corr_input

Validates and normalises input for correlation computations. Accepts either a
numeric matrix or a data frame, filters numeric columns, checks dimensions and
(optionally) missing values, and returns a numeric (double) matrix with
preserved column names.

internal

Compute correlation, association, and agreement measures for
small to high-dimensional datasets through a consistent matrix-oriented
interface. Supports classical correlations (Pearson, Spearman, Kendall),
distance correlation, partial correlation with regularised estimators,
shrinkage correlation for p >= n settings, robust correlations including
biweight mid-correlation, percentage-bend, and skipped correlation,
latent-variable methods for binary and ordinal data, repeated-measures
correlation, and agreement analyses based on Bland-Altman methods and
Lin's concordance correlation coefficient, including repeated-measures
extensions. 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>.

Thiago de Paula Oliveira

matrixCorr

Collection of Correlation and Association Estimators

matrixCorr-internal function

<dl><dt>data</dt>
<dd>A matrix or data frame. Non-numeric columns are dropped
(data.frame path). For matrix input, storage mode must be integer or double.</dd>
<dt>check_na</dt>
<dd>Logical (default <code>TRUE</code>). If <code>TRUE</code>, validate and
reject inputs containing <code>NA</code>/<code>NaN</code>/<code>Inf</code>. Set to
<code>FALSE</code> when an upstream routine (e.g., pairwise-complete kernels)
will handle missingness per pair.</dd></dl>

Arguments

Author

Validation and normalisation for correlation — matrixCorr-internal

<dl>

<dt>data</dt>
<dd>A matrix or data frame. Non-numeric columns are dropped
(data.frame path). For matrix input, storage mode must be integer or double.</dd>


<dt>check_na</dt>
<dd>Logical (default <code>TRUE</code>). If <code>TRUE</code>, validate and
reject inputs containing <code>NA</code>/<code>NaN</code>/<code>Inf</code>. Set to
<code>FALSE</code> when an upstream routine (e.g., pairwise-complete kernels)
will handle missingness per pair.</dd>

</dl>

matrixCorr-internal: Validation and normalisation for correlation

Description

Usage

Value

Arguments

Author

Details

See Also