If the argument

`k = 0`

is supplied to`kgaps()`

then an estimate of 1 is returned for the extremal index for any input data. For this very special case the estimated standard error associated with this estimate is set to zero and confidence intervals have a width of zero.Corrected a typing error in the description of

`uprob`

in the documentation for`plot.choose_uk()`

and`plot.choose_ud()`

.The unnecessary C++11 specification has been dropped to avoid a CRAN Package Check NOTE.

README.md: Used app.codecov.io as base for codecov link.

Create the help file for the package correctly, with alias exdex-package.

- A new estimator has been implemented, based on what we will call the D-gaps model of Holesovsky, J. and Fusek, M. Estimation of the extremal index using censored distributions. Extremes 23, 197–213 (2020). doi: 10.1007/s10687-020-00374-3

The value returned by

`nobs.kgaps()`

was incorrect in cases where there are censored K-gaps that are equal to zero. These K-gaps should not contribute to the number of observations. This has been corrected.In cases where the data used in

`kgaps`

are split into separate sequences, the threshold exceedance probability is estimated using all the data rather than locally within each sequence.A

`logLik`

method for objects inheriting from class`"kgaps"`

has been added.In the (unexported, internal) function

`kgaps_conf_int()`

the limits of the confidence intervals for the extremal index based on the K-gaps model are constrained manually to (0, 1) to avoid problems in calculating likelihood-based confidence intervals in cases where the the log-likelihood is greater than the interval cutoff when theta = 1.In the documentation of the argument

`k`

to`kgaps()`

it is noted that in practice`k`

should be no smaller than 1.The function

`kgaps()`

also return standard errors based on the expected information.In the package manual related functions have been arranged in sections for easier reading.

Activated 3rd edition of the

`testthat`

package

- The functions
`kgaps()`

,`kgaps_imt()`

and`choose_uk()`

can now accept a`data`

argument that- is a matrix of independent subsets of data, such as monthly or seasonal time series from different years,
- contains missing values, that is,
`NA`

s.

- A new dataset
`cheeseboro`

is included, which is a matrix containing some missing values. - In addition to
`kgaps()`

, the functions`kgaps_imt()`

and`choose_uk()`

now have an extra argument`inc_cens`

, which allows contributions from censored K-gaps to be included in the log-likelihood for the extremal index. - The default value of
`inc_cens`

in`kgaps()`

(and in`kgaps_imt()`

and`choose_uk()`

) is now`inc_cens = TRUE`

.

- Plot and print methods have been added for objects of class
`"confint_gaps"`

returned from`confint.kgaps()`

. - In
`confint.spm()`

and`confint.kgaps()`

the input confidence`level`

is included in the output object.

- An overloading ambiguity has been corrected to ensure installation on Solaris.