A function to generate Q-Q plots (from simulations) for the Anscombe and (binomial) Haar-Fisz transforms.

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`intensity` |
an Bernoulli intensity vector, e.g. pintens. |

`binsize` |
a binomial size to generate a binomial mean vector. |

`paths` |
the number of paths sampled from the mean vector to use in Q-Q calculations. |

`respaths` |
the number of residual paths to use in squared residual calculations. |

`plot.q` |
A boolean variable, indicating whether simulation Q-Q plots should be outputted or not. |

`plot.sq` |
A boolean variable, indicating whether simulation squared residual plots should be outputted or not. |

respaths paths are sampled from the mean intensity vector. From these, the first paths are used to generate Q-Q data, which are then averaged for the Q-Q plots. The original paths are used to calculate a squared residual vector corresponding to the mean intensity vector.

qqinfo. A 8 component list of quantile and residual plot information.

`vmat` |
A matrix of dimensions respathsxlength(intensity), each row being a path from the intensity vector. |

`Av` |
A matrix of dimensions respathsxlength(intensity), each row an Anscombe-transformed path. |

`bfv` |
A matrix of dimensions respathsxlength(intensity), each row a binomial Haar-Fisz-transformed path. |

`vminusl` |
A matrix of the difference between the paths and the mean intensity. |

`vminusl` |
A matrix of the difference between the Anscombe-transformed paths and the mean intensity. |

`vminusl` |
A matrix of the difference between the binomial Haar-Fisz-transformed paths and the mean intensity. |

`Asqres` |
vector of squared residuals of Anscombe-transformed paths. |

`bfsqres` |
vector of squared residuals of binomial Haar-Fisz-transformed paths. |

This function requires the package wavethresh. N.B. Since this function returns a lot of information, assign the output to a variable, to avoid printing endless information in the console.

Matt Nunes (m.nunes@ucl.ac.uk)

`qqnormy`

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Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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