evd | R Documentation |
S3 alogLik
method to perform loglikelihood adjustment for fitted
extreme value model objects returned from the functions
fgev
and fpot
in the evd package.
If x
is returned from fgev
then the call must
have used prob = NULL
.
## S3 method for class 'evd'
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 a vector of length 5. The first 3 components are
c("lax", "chandwich", "evd")
.
The remaining 2 components depend on the model that was fitted.
If fgev
was used then these components are
c("gev", "stat")
if nsloc
was NULL
and
c("gev", "nonstat")
if nsloc
was not NULL
.
If fpot
was used then these components are
c("pot", "gpd")
if model
was "gpd"
and
c("pot", "pp")
if model
was "pp"
.
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 evd package
got_evd <- requireNamespace("evd", quietly = TRUE)
if (got_evd) {
library(evd)
# An example from the evd::fgev documentation
set.seed(3082019)
uvdata <- evd::rgev(100, loc = 0.13, scale = 1.1, shape = 0.2)
M1 <- evd::fgev(uvdata, nsloc = (-49:50)/100)
adj_fgev <- alogLik(M1)
summary(adj_fgev)
# An example from Chandler and Bate (2007)
owfit <- fgev(ow$temp, nsloc = ow$loc)
adj_owfit <- alogLik(owfit, cluster = ow$year)
summary(adj_owfit)
# An example from the evd::fpot documentation
set.seed(3082019)
uvdata <- evd::rgpd(100, loc = 0, scale = 1.1, shape = 0.2)
M1 <- fpot(uvdata, 1)
adj_fpot <- alogLik(M1)
summary(adj_fpot)
# Fit using the pp model, rather than the gpd
M1 <- fpot(uvdata, 1, model = "pp", npp = 365)
adj_fpot <- alogLik(M1)
summary(adj_fpot)
}
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