gfigpd1: Fiducial inference for the generalized Pareto model with...

In gfiExtremes: Generalized Fiducial Inference for Extremes

Description

Runs the MCMC sampler of the fiducial distribution for the generalized Pareto model with known threshold.

Usage

gfigpd1(
  X,
  beta,
  threshold,
  gamma.init = NA,
  sigma.init = NA,
  sd.gamma = NA,
  sd.sigma = NA,
  Jnumb = 50L,
  iter = 10000L,
  burnin = 2000L,
  thin = 6L,
  nchains = 4L,
  nthreads = parallel::detectCores(),
  seeds = NULL
)

Arguments

X	numeric vector of data
beta	vector of probabilities corresponding to the quantiles to be estimated
threshold	value of the known threshold, must be smaller than the maximum of X
gamma.init	starting value for gamma in the MCMC
sigma.init	starting value for sigma in the MCMC
sd.gamma	standard deviation for the proposed gamma in the MCMC
sd.sigma	standard deviation for the proposed sigma in the MCMC
Jnumb	number of subsamples that are taken from the Jacobian
iter	number of iterations per chain (burnin excluded)
burnin	number of the first MCMC iterations discarded
thin	thinning number for the MCMC chain. (e.g. if it is 1 no iteration is skipped)
nchains	number of MCMC chains to run
nthreads	number of threads to run the chains in parallel
seeds	the seeds used for the MCMC sampler; one seed per chain, or NULL to use random seeds

Value

An object of class mcmc if nchains=1, otherwise an object of class mcmc.list.

References

Damian V. Wandler & Jan Hannig. Generalized fiducial confidence intervals for extremes. Extremes (2012) 15:67–87. <doi:10.1007/s10687-011-0127-9>

Examples

set.seed(666L)
X <- rgpareto(200L, mu = 10, gamma = 0.5, sigma = 1)
gf <- gfigpd1(
  X, beta = c(0.98, 0.99), threshold = 10, 
  iter = 2000L, nchains = 2L, nthreads = 2L
) # note: 2*2000 iterations is not enough, I'm using these settings because 
  # of CRAN constraints (elapsed time must be < 5s)
summary(gf)
qgpareto(c(0.98, 0.99), mu = 10, gamma = 0.5, sigma = 1)
rejectionRate(gf)
HPDinterval(gf)
HPDinterval(joinMCMCchains(gf))

gfiExtremes documentation built on Nov. 26, 2020, 5:07 p.m.