The CRAN Task
View on Extreme Value Analysis provides information about R packages
that perform various extreme value analyses. The lax package
supplements the univariate extreme value modelling, including regression
modelling, provided by 9 of these packages, namely eva, evd, evir, extRemes, fExtremes, ismev, mev, POT and texmex.
lax works in an object-oriented way, operating on R objects
returned from functions in other packages that summarise the fit of an
extreme value model. It uses the chandwich
package to provide robust sandwich estimation of parameter covariance
matrix and loglikelihood adjustment for models fitted by maximum
likelihood estimation. This is performed by an alogLik S3
method, illustrated by the following example.
This example is based on the analysis presented in Section 5.2 of Chandler and Bate
(2007). The data, which are available in the data frame
ow, are a bivariate time series of annual maximum
temperatures, recorded in degrees Fahrenheit, at Oxford and Worthing in
England, for the period 1901 to 1980. If interest is only in the
marginal distributions of high temperatures in Oxford and Worthing, then
we might fit a GEV regression model in which some or all of the
parameters may vary between Oxford and Worthing. However, we should
adjust for the cluster dependence between temperatures recorded during
the same year.
The following code fits such a model using the evm
function in the texmex package and
the uses alogLik to perform adjusted inferences.
library(lax)
library(texmex, quietly = TRUE)
# Fit a GEV model with separate location, scale and shape for Oxford and Worthing
# Note: phi = log(scale)
evm_fit <- evm(temp, ow, gev, mu = ~ loc, phi = ~ loc, xi = ~loc)
# Adjust the loglikelihood and standard errors
adj_evm_fit <- alogLik(evm_fit, cluster = ow$year, cadjust = FALSE)
# MLEs, SEs and adjusted SEs
summary(adj_evm_fit)
#> MLE SE adj. SE
#> mu: (Intercept) 81.17000 0.32820 0.40360
#> mu: loc 2.66800 0.32820 0.21280
#> phi: (Intercept) 1.30600 0.06091 0.06490
#> phi: loc 0.14330 0.06091 0.05074
#> xi: (Intercept) -0.19900 0.04937 0.03943
#> xi: loc -0.08821 0.04937 0.03624An object returned from aloglik is a function to
evaluate the adjusted loglikelihood, with anova,
coef, confint, logLik,
nobs, plot, print,
summary and vcov methods.
To get the current released version from CRAN:
install.packages("lax")See vignette("lax-vignette", package = "lax") for an
overview of the package.