Description Usage Arguments Details Note Author(s)

Function to convert a correlation matrix to a covariance matrix.

1 |

`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 |

This function was copied from package MBESS.

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 1s 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).

Ken Kelley (University of Notre Dame; KKelley@ND.Edu), Keke Lai

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