Methods for objects of class c("spm", "exdex") returned from
spm.
Usage
# S3 method for class 'spm'
coef(
object,
maxima = c("sliding", "disjoint"),
estimator = "all",
constrain = FALSE,
...
)
# S3 method for class 'spm'
vcov(object, maxima = c("sliding", "disjoint"), estimator = "all", ...)
# S3 method for class 'spm'
nobs(object, maxima = c("sliding", "disjoint"), ...)
# S3 method for class 'spm'
print(x, digits = max(3L, getOption("digits") - 3L), ...)
# S3 method for class 'spm'
summary(object, digits = max(3, getOption("digits") - 3L), ...)
# S3 method for class 'summary.spm'
print(x, ...)Arguments
- object
an object of class
"spm", a result of a call tospm.- maxima
A character scalar specifying whether to return the number of observed sliding maxima or disjoint maxima.
- estimator
A character vector specifying which of the three variants of the semiparametric maxima estimator to use:
"N2015", "BB2018"or"BB2018b". Seespmfor details. Ifestimator = "all"then the estimated variances of all variants are returned.- constrain
A logical scalar. If
constrain = TRUEthen any estimates that are greater than 1 are set to 1, that is, they are constrained to lie in (0, 1]. Otherwise, estimates that are greater than 1 may be obtained.- ...
For
print.summary.spm, additional arguments passed toprint.default.- x
print.spm. An object of classc("spm", "exdex"), a result of a call tospm.print.summary.spm. An object of class"summary.spm", a result of a call tosummary.spm.- digits
An integer. Used for number formatting with
signif.
Value
coef.spm. A numeric scalar (or a vector of length 3 if
estimator = "all"): the required estimate(s) of the extremal index
\(\theta\).
vcov.spm. A \(1 \times 1\) numeric matrix if
estimator = "N2015" or "BB2018" and a vector of length 3 if
estimator = "all", containing the estimated variance(s) of the
estimator(s).
nobs.spm. A numeric scalar: the number of observations used in the
fit.
print.spm. The argument x, invisibly.
summary.spm. Returns an object (a list) of class
"summary.spm" containing the list element object$call and a
numeric matrix matrix giving, for all three variants of the
semiparametric estimator and both sliding and disjoint blocks,
the (bias-adjusted) Estimate of the extremal index \(\theta\),
the estimated standard error (Std. Error),
and the bias adjustment (Bias adj.) applied to obtain the estimate, i.e.
the value subtracted from the raw estimate. If any of the
(bias-adjusted) estimates are greater than 1 then a column
containing the unconstrained estimates (Uncon. estimate) is added.
print.summary.spm. The argument x, invisibly.
Details
print.spm prints the original call to spm
and the estimates of the extremal index \(\theta\), based on all three
variants of the semiparametric maxima estimator and both sliding
and disjoint blocks.
Examples
See the examples in spm.
See also
spm for semiparametric estimation of the
extremal index based on block maxima.