lin.cor: Linear Correlation

In philentropy: Similarity and Distance Quantification Between Probability Functions

Linear Correlation

Description

This function computed the linear correlation between two vectors or a correlation matrix for an input matrix.

The following methods to compute linear correlations are implemented in this function:

Usage

lin.cor(
  x,
  y = NULL,
  method = "pearson",
  test.na = FALSE,
  epsilon = 1e-05,
  num.threads = NULL
)

Arguments

x	a numeric vector, matrix, or data.frame.
y	a numeric vector that should be correlated with x.
method	the method to compute the linear correlation between x and y.
test.na	a boolean value indicating whether input data should be checked for NA values.
epsilon	a small value to address cases where division by zero occurs. Default is '0.00001'. This is only used for 'method = "pearson"'.
num.threads	an integer specifying the number of threads to be used for parallel computations. Default is 'NULL', which uses the value from the 'RCPP_PARALLEL_NUM_THREADS' environment variable or '2' if not set.

Details

• method = "pearson" : Pearson's correlation coefficient (centred).

• method = "pearson2" : Pearson's uncentred correlation coefficient.

• method = "sq_pearson" . Squared Pearson's correlation coefficient.

• method = "kendall" : Kendall's correlation coefficient.

• method = "spearman" : Spearman's correlation coefficient.

Further Details:

• Pearson's correlation coefficient (centred) :

Author(s)

Hajk-Georg Drost

philentropy documentation built on Nov. 5, 2025, 5:11 p.m.