Most distributions are used for modelling either minima or maxima. Sometimes a better fit can be achieved by reversing the distribution. This functions helps to decide if the reversed distribution is advisable.

1 2 3 | ```
check_distribution(extreme = c("minimum", "maximum"), distribution,
def = list(minimum = c(),
maximum = c("gev")))
``` |

`extreme` |
character vector, describing the kind of extreme value to be fitted. Either |

`distribution` |
character vector of length one. Distribution chosen by the user. |

`def` |
a list of length two, containing the elements |

a character vector as long as `distribution`

containing the optimal choice for the given `distribution`

s under the constraints of `def`

.

1 2 3 4 5 6 | ```
# Using the Weibull distribution for minimum values is a good choice
check_distribution(extreme = "minimum", distribution = "wei")
# ... whereas the GEV is meant for maxima.
# Therefore the reversed distribution is suggested.
check_distribution(extreme = "minimum", distribution = "gev")
``` |

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