A covariance matrix used in structural equation modeling should be positive-definite, as it is going to be inverted during estimation and fit. This function checks whether a Hermitian matrix is positive-definite.

1 | ```
is.pd(covmat)
``` |

`covmat` |
A Hermitian matrix. |

This function checks, in this order:

1. Matrix is Hermitian

2. All covariances are within bounds

3. See if matrix is invertible using `solve`

4. Check if all eigenvalues are positive

5. Check whether the determinant is positive

TRUE or FALSE.

`is.within.bounds`

and `is.hermitian`

.

1 2 |

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