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 |

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).

Ken Kelley (University of Notre Dame; [email protected]), Keke Lai

MBESS documentation built on Jan. 11, 2018, 1:08 a.m.

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