BigDataStatMeth (version 2.0.3)

bdCorr_matrix: Compute correlation matrix for in-memory matrices (unified function)

Description

Compute Pearson or Spearman correlation matrix for matrices that fit in memory. This function automatically detects whether to compute:

• Single matrix correlation cor(X) - when only matrix X is provided

• Cross-correlation cor(X,Y) - when both matrices X and Y are provided

Usage

bdCorr_matrix(
  X,
  Y = NULL,
  trans_x = NULL,
  trans_y = NULL,
  method = NULL,
  use_complete_obs = NULL,
  compute_pvalues = NULL,
  threads = NULL
)

Value

A list containing correlation results

Arguments

X

First numeric matrix (observations in rows, variables in columns)

Y

Second numeric matrix (optional, observations in rows, variables in columns)

trans_x

Logical, whether to transpose matrix X (default: FALSE)

trans_y

Logical, whether to transpose matrix Y (default: FALSE, ignored if Y not provided)

method

Character string indicating correlation method ("pearson" or "spearman", default: "pearson")

use_complete_obs

Logical, whether to use only complete observations (default: TRUE)

compute_pvalues

Logical, whether to compute p-values for correlations (default: TRUE)

threads

Integer, number of threads for parallel computation (optional, default: -1 for auto)

Examples

# \donttest{
set.seed(123)
X <- matrix(rnorm(1000), nrow = 100, ncol = 10)

# Single matrix correlation
res <- bdCorr_matrix(X)

# Transposed (sample-sample correlations)
res_t <- bdCorr_matrix(X, trans_x = TRUE)

# Cross-correlation with a second matrix
Y <- matrix(rnorm(400), nrow = 100, ncol = 4)
res_xy <- bdCorr_matrix(X, Y)
# }