Assumes a uniform distribution on the shape parameter `zeta`

and an
exponential distribution on the scale parameter `eta`

. To be used
as prior for `Model.additivelink.exponential.fitness`

.

1 2 | ```
Model.fitness.genlambdaparprior(shapemin = 0.75, shapemax = 1.5, ratescale,
sdshapeprob = 0.1, sdpropscale = 0.1)
``` |

`shapemin` |
Minimal Value of the shape parameter. Default: 0.75. |

`shapemax` |
Maximal Value of the shape parameter. Default: 1.5. |

`ratescale` |
Rate parameter for the prior distribution of the scale parameter. In the model this is on the same scale as the entries of |

`sdshapeprob` |
Standard deviation for the additivel normally distributed random walk proposal for the shape parameter. Defaults to 0.1. |

`sdpropscale` |
Standard deviation for the multiplicative lognormal proposals for the scale parameter. |

list of functions necessary for constructing Metropolis-Hastings updates.

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