Methods for objects of class "blite" returned from
blite. confint.blite is a misnomer: it returns
(equi-tailed) Bayesian credible intervals.
# S3 method for blite
plot(x, which = c("all", "pu", "gp", "xi", "theta"), ...)
# S3 method for blite
coef(object, fun, ...)
# S3 method for blite
vcov(object, ...)
# S3 method for blite
nobs(object, ...)
# S3 method for blite
summary(
object,
short = TRUE,
mean = TRUE,
digits = max(3, getOption("digits") - 3L),
...
)
# S3 method for summary.blite
print(x, ...)
# S3 method for blite
confint(object, parm = "all", level = 0.95, ...)An object inheriting from class "blite", a result of a
call to blite.
A character scalar indicating which plot(s) to produce.
If which = "all" then all 4 plots described in Details
are produced. Otherwise, only one of these plots is produced, with the
possible names of the arguments being in the order that the plots are
described in Details.
For plot.blite: arguments passed to
plot, such as graphical parameters.
For coef.blite: additional arguments passed to fun.
For print.summary.blite: additional arguments passed to
print.default.
Otherwise ... is unused.
An object of class "blite", returned by
blite.
A summary function to be applied to each column of the simulated
values in object. If fun is missing then
mean is used.
A logical scalar that determines the form of the output. See Details.
A logical scalar. Determines the form of the output if
short = TRUE. See Details.
An integer. Passed to signif to
round the values in the summary.
A character vector specifying the parameters for which
confidence intervals are required. The default, which = "all",
produces confidence intervals for all the parameters, that is,
\(p\)u,
\(\sigma\)u,
\(\xi\) and \(\theta\). If which = "gp" then intervals are
produced only for
\(\sigma\)u and
\(\xi\). Otherwise, parm must be a subset of
c("pu", "sigmau", "xi", "theta").
The credible level required. A numeric scalar in (0, 1).
plot.blite: No return value, only the plot is produced.
coef.blite: a numeric vector of length 4 with names
c("p[u]", "sigma[u]", "xi", "theta"). The values of summary
statistics calculated using the function fun.
vcov.blite: a \(4 \times 4\) matrix with row and
column names c("p[u]", "sigma[u]", "xi", "theta"). An estimate
of the posterior covariance matrix, calculated using
cov.
nobs.blite: a numeric vector of length 3 with names
c("p[u]", "gp", "theta"). The respective number of observations
used to infer \(p\)u,
(\(\sigma\)u,
\(\xi\)) and \(\theta\).
summary.blite: an object containing the original function call and
a matrix of summaries of the posterior samples for each of the
parameters. If short = TRUE then there are 2 columns, containing
either the sample posterior means and standard deviations
(mean = TRUE) or the sample posterior medians and inter-quartile
ranges (mean = FALSE). If short = FALSE then there are 4
columns, with each column containing the usual 6-number summary produced
by summary. The object is printed by
print.summary.blite.
print.summary.blite: the argument x is returned, invisibly.
confint.blite: a numeric matrix with 2 columns giving the lower and
upper credible limits for each parameter. These columns are labelled
as (1-level)/2 and 1-(1-level)/2, expressed as a
percentage, by default 2.5% and 97.5%. The row names
are the names of the parameters supplied in parm.
For plot.blite, if which = "all" then 4 plots are produced.
Top left: histogram of the posterior sample for the threshold exceedance probability \(p\)u.
Top right: scatter plot of posterior sample for the GP parameters (\(\sigma\)u, \(\xi\)). The linear constraint \(\xi\) > -\(\sigma\)u / \(x\) (n) is drawn on the plot.
Bottom left: histogram of the posterior sample for the GP shape parameter \(\xi\).
Bottom right: histogram of the posterior sample for the extremal index \(\theta\).
blite to perform frequentist threshold-based
inference for time series extremes.
predict.blite: for predictive inference for the
largest value observed in \(N\) years.