Description Usage Arguments Value

View source: R/reconstitute_cov.R

This takes a vector of upper diagonal terms and reconstitutes it into the matrix you want in the end. The first term is always 1 under the assumptions of the IV hurdle models. If you did a cholesky decomposition it will un-do that tranformation for you.

1 | ```
reconstitute.cov(vals, num, chol = myChol)
``` |

`vals` |
a vector of covariance matrix elements |

`num` |
the number of endogenous regressors |

`chol` |
True/False. If true, will re-transform to original |

The vector renamed according to what it needs to be to work in the likelihood functions

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