S3 `alogLik`

method to perform loglikelihood adjustment for fitted
extreme value model objects returned from
`fitGPD`

function in the POT package.
The model must have been fitted using maximum likelihood estimation.

```
# S3 method for uvpot
alogLik(x, cluster = NULL, use_vcov = TRUE, ...)
```

- x
A fitted model object with certain associated S3 methods. See

**Details**.- cluster
A vector or factor indicating from which cluster the respective log-likelihood contributions from

`loglik`

originate. The length of`cluster`

must be consistent with the`estfun`

method to be used in the estimation of the 'meat'`V`

of the sandwich estimator of the covariance matrix of the parameters to be passed to`adjust_loglik`

. In most cases,`cluster`

must have length equal to the number of observations in data. The exception is the GP (only) model (`binom = FALSE`

), where the`cluster`

may either contain a value for each observation in the raw data, or for each threshold exceedance in the data.If

`cluster`

is not supplied (is`NULL`

) then it is assumed that each observation forms its own cluster. See**Details**for further details.- use_vcov
A logical scalar. Should we use the

`vcov`

S3 method for`x`

(if this exists) to estimate the Hessian of the independence loglikelihood to be passed as the argument`H`

to`adjust_loglik`

? Otherwise,`H`

is estimated inside`adjust_loglik`

using`optimHess`

.- ...
Further arguments to be passed to the functions in the sandwich package

`meat`

(if`cluster = NULL`

), or`meatCL`

(if`cluster`

is not`NULL`

).

An object inheriting from class `"chandwich"`

. See

`class(x)`

is `c("lax", "chandwich", "POT", "pot", "gpd")`

.

See `alogLik`

for details.

Chandler, R. E. and Bate, S. (2007). Inference for clustered
data using the independence loglikelihood. *Biometrika*,
**94**(1), 167-183. doi:10.1093/biomet/asm015

Suveges, M. and Davison, A. C. (2010) Model
misspecification in peaks over threshold analysis, *The Annals of
Applied Statistics*, **4**(1), 203-221.
doi:10.1214/09-AOAS292

Zeileis (2006) Object-Oriented Computation and Sandwich
Estimators. *Journal of Statistical Software*, **16**, 1-16.
doi:10.18637/jss.v016.i09

`alogLik`

: loglikelihood adjustment for model fits.

```
# We need the POT package
got_POT <- requireNamespace("POT", quietly = TRUE)
#> Registered S3 methods overwritten by 'POT':
#> method from
#> print.bvpot evd
#> plot.bvpot evd
if (got_POT) {
library(POT)
# An example from the POT::fitgpd documentation.
set.seed(4082019)
x <- POT::rgpd(200, 1, 2, 0.25)
fit <- fitgpd(x, 1, "mle")
adj_fit <- alogLik(fit)
}
#>
#> Attaching package: 'POT'
#> The following objects are masked from 'package:fExtremes':
#>
#> dgpd, pgpd, qgpd, rgpd
#> The following objects are masked from 'package:evir':
#>
#> dgpd, pgpd, qgpd, rgpd
#> The following objects are masked from 'package:eva':
#>
#> dgpd, pgpd, qgpd, rgpd
#> The following object is masked from 'package:extRemes':
#>
#> mrlplot
#> The following objects are masked from 'package:evd':
#>
#> dens, dgpd, exiplot, mrlplot, pgpd, pp, qgpd, qq, rgpd, tcplot
```