Description Usage Arguments Details Value Author(s) See Also

It produces diagnostic plots based on (randomised) quantile residuals.

1 2 3 4 | ```
post.check(x, main = "Histogram and Density Estimate of Residuals",
main2 = "Histogram and Density Estimate of Residuals",
xlab = "Quantile Residuals", xlab2 = "Quantile Residuals",
intervals = FALSE, n.sim = 100, prob.lev = 0.05, ...)
``` |

`x` |
A fitted |

`main` |
Title for the plot. |

`main2` |
Title for the plot in the second row. This comes into play only when fitting models with two non-binary margins. |

`xlab` |
Title for the x axis. |

`xlab2` |
Title for the x axis in the second row. As above. |

`intervals` |
If |

`n.sim` |
Number of replicate datasets used to simulate quantiles of the residual distribution. |

`prob.lev` |
Overall probability of the left and right tails of the probabilities' distributions used for interval calculations. |

`...` |
Other graphics parameters to pass on to plotting commands. |

If the model fits the response well then the plots should look normally distributed.
When fitting models with discrete and/or continuous margins, four plots will be produced. In this case,
the arguments `main2`

and `xlab2`

come into play and allow for different
labelling across the plots.

`qr` |
It returns the (randomised) quantile residuals for the continuous or discrete margin when fitting a model that involves a binary response. |

`qr1` |
As above but for first equation (this applies when fitting models with continuous/discrete margins). |

`qr2` |
As above but for second equation. |

Maintainer: Giampiero Marra [email protected]

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