Package: texmex
Type: Package
Title: Statistical Modelling of Extreme Values
Version: 2.4.9
Date: 2024-03-04
Authors@R: c(person("Harry", "Southworth", role=c("aut", "cre"),
                    email="harry.southworth@gmail.com"),
             person(c("Janet", "E."), "Heffernan", role="aut"),
             person(c("Paul", "D."), "Metcalfe", role="aut",
                    ,email="paul.metcalfe@gmail.com"),
             person("Yiannis", "Papastathopoulos", role="ctb"),
             person("Alec", "Stephenson", role="ctb"),
             person("Stuart", "Coles", role="ctb"))
Author: Harry Southworth [aut, cre],
  Janet E. Heffernan [aut],
  Paul D. Metcalfe [aut],
  Yiannis Papastathopoulos [ctb],
  Alec Stephenson [ctb],
  Stuart Coles [ctb]
Maintainer: Harry Southworth <harry.southworth@gmail.com>
Description: Statistical extreme value modelling of threshold excesses, maxima
    and multivariate extremes. Univariate models for threshold excesses and maxima
    are the Generalised Pareto, and Generalised Extreme Value model respectively.
    These models may be fitted by using maximum (optionally penalised-)likelihood,
    or Bayesian estimation, and both classes of models may be fitted with covariates
    in any/all model parameters. Model diagnostics support the fitting process.
    Graphical output for visualising fitted models and return level estimates is
    provided. For serially dependent sequences, the intervals declustering algorithm
    of Ferro and Segers (2003) <doi:10.1111/1467-9868.00401> is provided, with
    diagnostic support to aid selection of threshold and declustering horizon.
    Multivariate modelling is performed via the conditional approach of Heffernan
    and Tawn (2004) <doi:10.1111/j.1467-9868.2004.02050.x>, with graphical tools for
    threshold selection and to diagnose estimation convergence.
License: GPL (>= 2)
Depends: mvtnorm, ggplot2, stats
Suggests: MASS, gridExtra, parallel, lattice, knitr, rmarkdown, dplyr,
        tidyr, testthat, devtools, survival, ismev
Imports: Rcpp (>= 0.12.18)
LinkingTo: Rcpp
LazyLoad: yes
LazyData: yes
URL: https://github.com/harrysouthworth/texmex
RoxygenNote: 7.2.3
Encoding: UTF-8
VignetteBuilder: knitr
Collate: 'AIC.evm.R' 'Dcond.R' 'Profile_likelihood_HT_unc.R'
        'Profile_likelihood_cd_nm_joint_D_KT.R'
        'Profile_likelihood_cd_nm_joint_D_KT_neg.R' 'RcppExports.R'
        'bootmex.R' 'gpd.sandwich.R' 'gpd.info.R' 'texmexFamily.R'
        'cgpd.R' 'chi.R' 'coef.evmSim.R' 'coefficients.evm.R'
        'coefficients.migpd.R' 'constructObject.R' 'copulas.R' 'cv.R'
        'degp3.R' 'dgev.R' 'dgpd.R' 'efficient.closures.R' 'egp3.R'
        'egp3RangeFit.R' 'endPoint.R' 'estimate_HT.R'
        'estimate_HT_KPT_joint_posneg_nm.R' 'evm.R' 'evm.simSetSeed.R'
        'evmBoot.R' 'evmFit.R' 'evmSim.R' 'extremalIndex.R' 'gev.R'
        'ggplot.bayes.R' 'ggplot.boot.R' 'ggplot.cluster.R'
        'ggplot.evm.R' 'ggplot.mex.R' 'ggplot.migpd.R'
        'ggplot.predict.R' 'ggplot.thresh.R' 'glo.R'
        'globalVariables.R' 'gpd.R' 'gpdProfileLikRetLevels.R'
        'gpdRangeFit.R' 'gumbel.R' 'hist.evm.R' 'initial_posneg.R'
        'jointExceedanceCurves.R' 'mex.R' 'mexDependence.R'
        'mexDependenceLowLevelFunctions.R' 'mexMonteCarlo.R'
        'mexRangeFit.R' 'mexTransform.R' 'migpd.R' 'migpdCoefs.R'
        'mrl.R' 'mspearman.R' 'multivariate.cauchy.R' 'pegp3.R'
        'pgev.R' 'pgpd.R' 'plot.bootmex.R' 'plot.evm.R' 'plot.evmSim.R'
        'plot.mex.R' 'plot.mexPrediction.R' 'plot.migpd.R'
        'plot.predict.link.evm.R' 'plotrl.evm.R' 'ppevm.R'
        'predict.evm.R' 'predict.mex.R' 'predictWorkers.R'
        'print.bootmex.R' 'print.evm.R' 'print.evmSim.R'
        'print.mexDependence.R' 'print.mexPrediction.R' 'print.migpd.R'
        'profile_minmax_joint_posneg_KT.R' 'qegp3.R' 'qgev.R' 'qgpd.R'
        'qgpd2.R' 'qqevm.R' 'rMaxAR.R' 'regp3.R' 'residuals.evm.R'
        'revTransform.R' 'rgev.R' 'rgpd.R' 'roots.R' 'simulate.R'
        'sombrero-internal.R' 'summary.evm.R' 'summary.evmSim.R'
        'summary.migpd.R' 'summary.predict.mex.R' 'texmex-package.R'
        'texmexWorkers.R' 'thinAndBurn.evm.sim.R' 'u2gpd.R'
        'weibull.info.R' 'weibull.R'
NeedsCompilation: yes
Packaged: 2024-03-04 16:20:59 UTC; harry
Repository: CRAN
Date/Publication: 2024-03-04 16:40:03 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 02:07:43 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
