evgam (version 1.0.2)

bgev2gev: Conversion between blended generalised extreme value distribution and generalised extreme value distribution parameters

Description

Conversion between location, scale and shape parameters of the generalised extreme value distribution and corresponding parameters of blended generalised extreme value distribution in both directions.

Usage

bgev2gev(
  location,
  scale,
  shape,
  pa = 0.05,
  pb = 0.2,
  alpha = 0.5,
  beta = 0.5,
  simplify = FALSE
)
gev2bgev(
  location,
  scale,
  shape,
  pa = 0.05,
  pb = 0.2,
  alpha = 0.5,
  beta = 0.5,
  simplify = FALSE
)

Value

A list or array if simplify = TRUE.

Arguments

location, scale, shape

location, scale and shape parameters.

pa, pb, alpha, beta

Gumbel to GEV mixing parameters; see Details.

simplify

logical; should simplify2array() be called at the end?

Details

The blended generalised extreme value distribution has location parameter \(q_\alpha\), scale \(s_\beta\) and shape \(\xi\) parameters; see, e.g., dbgev. The generalised extreme value distribution's location and scale parameters in its typical form are given by \(\mu = q_\alpha - s_\beta (\ell_{\alpha, \xi} - 1) / (\ell_{1 - \beta/2, \xi} - \ell_{\beta/2, \xi})\) and \(\sigma = \xi s_\beta / (\ell_{1 - \beta/2, \xi} - \ell_{\beta/2, \xi})\). So bgev2gev gives the mapping \((q_\alpha, s_\beta, \xi) \mapsto (\mu, \sigma, \xi))\). The reverse mapping, \((\mu, \sigma, \xi) \mapsto (q_\alpha, s_\beta, \xi))\), is given by gev2bgev.

References

Castro-Camilo, D., Huser, R., & Rue, H. (2022). Practical strategies for generalized extreme value-based regression models for extremes. Environmetrics, 33(6), e2742. tools:::Rd_expr_doi("10.1002/env.2742")

See Also

dbgev

Examples

bgev2gev(2, 1, .1)
gev2bgev(2, 1, .1)