Description Usage Arguments Value

Estimates a linear model with one endogenous variable using Gaussian copula. The optimization is done via maximum likelihood, using the BFLG algorithm.

1 | ```
copulaCont1(y, X, P, param = NULL, intercept = NULL)
``` |

`y` |
a vector or matrix containing the dependent variable. |

`X` |
a data frame or matrix containing the regressors of the model, both exogeneous and endogeneous. The last column should contain the endogeneous variable. |

`P` |
a vector containing the continuous, non-normally distributed endogeneous variable. |

`param` |
Initial values for the parameters to be optimized over. |

`intercept` |
Optional parameter. The model is estimated by default with
intercept. If no intercept is desired or the regressors matrix |

Returns a list with the best set of parameters found.

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