Description Value Author(s) See Also

A fitted gamlss object returned by function `gamlss`

and of class "gamlss" and "SemiParBIV".

`fit` |
List of values and diagnostics extracted from the output of the algorithm. |

`gam1, gam2, gam3` |
Univariate starting values' fits. |

`coefficients` |
The coefficients of the fitted model. |

`weights` |
Prior weights used during model fitting. |

`sp` |
Estimated smoothing parameters of the smooth components. |

`iter.sp` |
Number of iterations performed for the smoothing parameter estimation step. |

`iter.if` |
Number of iterations performed in the initial step of the algorithm. |

`iter.inner` |
Number of iterations performed within the smoothing parameter estimation step. |

`n` |
Sample size. |

`X1, X2, X3, ...` |
Design matrices associated with the linear predictors. |

`X1.d2, X2.d2, X3.d2, ...` |
Number of columns of |

`l.sp1, l.sp2, l.sp3, ...` |
Number of smooth components in the equations. |

`He` |
Penalized -hessian/Fisher. This is the same as |

`HeSh` |
Unpenalized -hessian/Fisher. |

`Vb` |
Inverse of |

`F` |
This is obtained multiplying Vb by HeSh. |

`t.edf` |
Total degrees of freedom of the estimated bivariate model. It is calculated as |

`edf1, edf2, edf3, ...` |
Degrees of freedom for the model's equations. |

`wor.c` |
Working model quantities. |

`eta1, eta2, eta3, ...` |
Estimated linear predictors. |

`y1` |
Response. |

`logLik` |
Value of the (unpenalized) log-likelihood evaluated at the (penalized or unpenalized) parameter estimates. |

Maintainer: Giampiero Marra [email protected]

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