spm_methods {exdex}

Methods for objects of class "spm"

Description

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 to spm.

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". See spm for details. If estimator = "all" then the estimated variances of all variants are returned.

constrain

A logical scalar. If constrain = TRUE then 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 to print.default.

x

print.spm. An object of class c("spm", "exdex"), a result of a call to spm.

print.summary.spm. An object of class "summary.spm", a result of a call to summary.spm.

digits

An integer. Used for number formatting with signif.

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.

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.

Examples

See the examples in spm.

See Also

spm for semiparametric estimation of the extremal index based on block maxima.