POT | R Documentation |
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 class '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 If |
use_vcov |
A logical scalar. Should we use the |
... |
Further arguments to be passed to the functions in the
sandwich package |
See alogLik
for details.
An object inheriting from class "chandwich"
. See
adjust_loglik
.
class(x)
is c("lax", "chandwich", "POT", "pot", "gpd")
.
Chandler, R. E. and Bate, S. (2007). Inference for clustered data using the independence loglikelihood. Biometrika, 94(1), 167-183. \Sexpr[results=rd]{tools:::Rd_expr_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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1214/09-AOAS292")}
Zeileis (2006) Object-Oriented Computation and Sandwich Estimators. Journal of Statistical Software, 16, 1-16. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v016.i09")}
alogLik
: loglikelihood adjustment for model fits.
# We need the POT package
got_POT <- requireNamespace("POT", quietly = TRUE)
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)
}
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