Informative GEV prior for GEV parameters (\(\mu, \sigma, \xi\))
constructed on the quantile scale. For information about how to set this
prior see set_prior.
gev_quant(pars, prob, shape, scale, min_xi = -Inf, max_xi = Inf, trendsd = 0)A numeric vector of length 3. GEV parameters (\(\mu, \sigma, \xi\)).
A numeric vector of length 3 containing exceedance
probabilities (\(p_1, p_2, p_3\)) such that
\(p_1 > p_2 > p_3\).
If the values in quant are not ordered from largest to smallest
then they will be ordered inside set_prior without warning.
Numeric vectors of length 3. Shape and scale
parameters specifying (independent) gamma prior distributions placed
on the differences between the quantiles corresponding to the
probabilities given in prob.
A numeric scalar. Prior lower bound on \(\xi\).
A numeric scalar. Prior upper bound on \(\xi\).
Has no function other than to achieve compatibility with function in the evdbayes package.
The log of the prior density.
See Coles and Tawn (1996) and/or Stephenson (2016) for details.
Note that the lower end point of the distribution of the distribution of the variable in question is assumed to be equal to zero. If this is not the case then the user should shift the data to ensure that this is true.
Coles, S. G. and Tawn, J. A. (1996) A Bayesian analysis of extreme rainfall data. Appl. Statist., 45, 463-478.
Stephenson, A. (2016) Bayesian inference for extreme value modelling. In Extreme Value Modeling and Risk Analysis: Methods and Applications (eds D. K. Dey and J. Yan), 257-280, Chapman and Hall, London. doi:10.1201/b19721 .