Function to convert a correlation matrix to a covariance matrix.
cor2cov(cor.mat, sd, discrepancy = 1e-05)
| cor.mat | the correlation matrix to be converted |
|---|---|
| sd | a vector that contains the standard deviations of the variables in the correlation matrix |
| discrepancy | a neighborhood of 1, such that numbers on the main diagonal of the correlation matrix will be considered as equal to 1 if they fall in this neighborhood |
The correlation matrix to convert can be either symmetric or triangular. The covariance matrix returned is always a symmetric matrix.
The correlation matrix input should be a square matrix, and the length of sd should be equal to the number of variables in the correlation matrix (i.e., the number of rows/columns). Sometimes the correlation matrix input may not have exactly 1's on the main diagonal, due to, eg, rounding; discrepancy specifies the allowable discrepancy so that the function still considers the input as a correlation matrix and can proceed (but the function does not change the numbers on the main diagonal).