Methods for objects of class "dgaps"

Source: R/dgaps_methods.R

Methods for objects of class c("dgaps", "exdex") returned from dgaps.

# S3 method for dgaps
coef(object, ...)

# S3 method for dgaps
vcov(object, type = c("observed", "expected"), ...)

# S3 method for dgaps
nobs(object, ...)

# S3 method for dgaps
logLik(object, ...)

# S3 method for dgaps
print(x, digits = max(3L, getOption("digits") - 3L), ...)

# S3 method for dgaps
summary(
  object,
  se_type = c("observed", "expected"),
  digits = max(3, getOption("digits") - 3L),
  ...
)

# S3 method for summary.dgaps
print(x, ...)

Arguments

object

and object of class c("dgaps", "exdex") returned from dgaps.

...

For print.summary.dgaps, additional arguments passed to print.default.

type

A character scalar. Should the estimate of the variance be based on the observed information or the expected information?

x

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

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

digits

print.dgaps. The argument digits to print.default.

summary.dgaps. An integer. Used for number formatting with signif.

se_type

A character scalar. Should the estimate of the standard error be based on the observed information or the expected information?

Value

coef.dgaps. A numeric scalar: the estimate of the extremal index

\(\theta\).

vcov.dgaps. A \(1 \times 1\) numeric matrix containing the estimated variance of the estimator.

nobs.dgaps. A numeric scalar: the number of inter-exceedance times used in the fit. If x$inc_cens = TRUE then this includes up to 2 censored observations.

logLik.dgaps. An object of class "logLik": a numeric scalar with value equal to the maximised log-likelihood. The returned object also has attributes nobs, the numbers of \(K\)-gaps that contribute to the log-likelihood and "df", which is equal to the number of total number of parameters estimated (1).

print.dgaps. The argument x, invisibly.

summary.dgaps. Returns a list containing the list element

object$call and a numeric matrix summary giving the estimate of the extremal index \(\theta\) and the estimated standard error (Std. Error).

print.summary.dgaps. The argument x, invisibly.

Examples

See the examples in dgaps.

See also

dgaps for maximum likelihood estimation of the extremal index \(\theta\) using the \(K\)-gaps model.

confint.dgaps for confidence intervals for \(\theta\).