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:
lin.cor(
x,
y = NULL,
method = "pearson",
test.na = FALSE,
epsilon = 1e-05,
num.threads = NULL
)a numeric vector, matrix, or data.frame.
a numeric vector that should be correlated with x.
the method to compute the linear correlation between x and y.
a boolean value indicating whether input data should be checked for NA values.
a small value to address cases where division by zero occurs. Default is `0.00001`. This is only used for `method = "pearson"`.
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.
Hajk-Georg Drost
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) :