kgaps_post {revdbayes} | R Documentation |
Random sampling from K-gaps posterior distribution
Description
Uses the rust
package to simulate from the posterior
distribution of the extremal index based on the K-gaps model
for threshold interexceedance times of Suveges and Davison (2010).
Usage
kgaps_post(
data,
thresh,
k = 1,
n = 1000,
inc_cens = TRUE,
alpha = 1,
beta = 1,
param = c("logit", "theta"),
use_rcpp = TRUE
)
Arguments
data |
A numeric vector or numeric matrix of raw data. If If |
thresh |
A numeric scalar. Extreme value threshold applied to data. |
k |
A numeric scalar. Run parameter |
n |
A numeric scalar. The size of posterior sample required. |
inc_cens |
A logical scalar indicating whether or not to include
contributions from right-censored inter-exceedance times, relating to the
first and last observations. It is known that these times are greater
than or equal to the time observed.
If |
alpha , beta |
Positive numeric scalars. Parameters of a
beta( |
param |
A character scalar. If |
use_rcpp |
A logical scalar. If |
Details
A beta(,
) prior distribution is used for
so that the posterior from which values are simulated is
proportional to
See kgaps_stat
for a description of the variables
involved in the contribution of the likelihood to this expression.
The ru
function in the rust
package simulates from this posterior distribution using the
generalised ratio-of-uniforms distribution. To improve the probability
of acceptance, and to ensure that the simulation will work even in
extreme cases where the posterior density of is unbounded as
approaches 0 or 1, we simulate from the posterior
distribution of
and then transform back to the
-scale.
Value
An object (list) of class "evpost"
, which has the same
structure as an object of class "ru"
returned from
ru
.
In addition this list contains
-
call
: The call tokgaps()
. -
model
: The character scalar"kgaps"
. -
thresh
: The argumentthresh
. -
ss
: The sufficient statistics for the K-gaps likelihood, as calculated bykgaps_stat
.
References
Suveges, M. and Davison, A. C. (2010) Model misspecification in peaks over threshold analysis, The Annals of Applied Statistics, 4(1), 203-221. doi:10.1214/09-AOAS292
See Also
ru
for the form of the object returned by
kgaps_post
.
dgaps_post
for Bayesian inference about the
extremal index using the
-gaps model.
Examples
# Newlyn sea surges
thresh <- quantile(newlyn, probs = 0.90)
k_postsim <- kgaps_post(newlyn, thresh)
plot(k_postsim)
### Cheeseboro wind gusts
k_postsim <- kgaps_post(exdex::cheeseboro, thresh = 45, k = 3)
plot(k_postsim)