Three quantiles, that is, the value of quantile and their respective exceedance probabilities, are provided. This function attempts to find the location, scale and shape parameters of a GEV distribution that has these quantiles.
quantile_to_gev(quant, prob)
A numeric vector of length 3. Values of the quantiles.
The values should increase with the index of the vector.
If not, the values in quant
will be sorted into increasing order
without warning.
A numeric vector of length 3. Exceedance probabilities
corresponding to the quantiles in quant
.
The values should decrease with the index of the vector.
If not, the values in prob
will be sorted into decreasing order
without warning.
A numeric vector of length 3 containing the GEV location, scale and shape parameters.
Suppose that \(G(x)\) is the distribution function of
a GEV(\(\mu, \sigma, \xi\)) distribution. This function attempts to
solve numerically the set of three non-linear equations
$$G(q_i) = 1 - p_i, i = 1, 2, 3$$
where \(q_i, i=1,2,3\) are the quantiles in quant
and
\(p_i, i=1,2,3\) are the exceedance probabilities in prob
.
This is reduced to a one-dimensional optimisation over the GEV
shape parameter.
rprior_quant
for simulation of GEV parameters from
a prior constructed on the quantile scale.