Prior distribution for eta and zeta in the fitness model

Description

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.

Usage

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

Arguments

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 L

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.

Value

list of functions necessary for constructing Metropolis-Hastings updates.

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