spm_methods | R Documentation |
"spm"
Methods for objects of class c("spm", "exdex")
returned from
spm
.
## 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, ...)
object |
an object of class |
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: |
constrain |
A logical scalar. If |
... |
For |
x |
|
digits |
An integer. Used for number formatting with
|
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.
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.
See the examples in spm
.
spm
for semiparametric estimation of the
extremal index based on block maxima.
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