{ "_id": "6a102cdaacfb0bcc41c93714", "Package": "texmex", "Type": "Package", "Title": "Statistical Modelling of Extreme Values", "Version": "2.4.9", "Date": "2024-02-28", "Authors@R": "c(person(\"Harry\", \"Southworth\", role=c(\"aut\", \"cre\"),\nemail=\"harry.southworth@gmail.com\"),\nperson(c(\"Janet\", \"E.\"), \"Heffernan\", role=\"aut\"),\nperson(c(\"Paul\", \"D.\"), \"Metcalfe\", role=\"aut\",\n,email=\"paul.metcalfe@gmail.com\"),\nperson(\"Yiannis\", \"Papastathopoulos\", role=\"ctb\"),\nperson(\"Alec\", \"Stephenson\", role=\"ctb\"),\nperson(\"Stuart\", \"Coles\", role=\"ctb\"))", "Author": "Harry Southworth [aut, cre], Janet E. Heffernan [aut], Paul D.\nMetcalfe [aut], Yiannis Papastathopoulos [ctb], Alec Stephenson\n[ctb], Stuart Coles [ctb]", "Maintainer": "Harry Southworth ", "Description": "Statistical extreme value modelling of threshold excesses,\nmaxima and multivariate extremes. Univariate models for\nthreshold excesses and maxima are the Generalised Pareto, and\nGeneralised Extreme Value model respectively. These models may\nbe fitted by using maximum (optionally penalised-)likelihood,\nor Bayesian estimation, and both classes of models may be\nfitted with covariates in any/all model parameters. Model\ndiagnostics support the fitting process. Graphical output for\nvisualising fitted models and return level estimates is\nprovided. For serially dependent sequences, the intervals\ndeclustering algorithm of Ferro and Segers (2003)\n is provided, with diagnostic\nsupport to aid selection of threshold and declustering horizon.\nMultivariate modelling is performed via the conditional\napproach of Heffernan and Tawn (2004)\n, with graphical tools\nfor threshold selection and to diagnose estimation convergence.", "License": "GPL (>=2)", "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'\n'Profile_likelihood_cd_nm_joint_D_KT.R'\n'Profile_likelihood_cd_nm_joint_D_KT_neg.R' 'RcppExports.R'\n'bootmex.R' 'gpd.sandwich.R' 'gpd.info.R' 'texmexFamily.R'\n'cgpd.R' 'chi.R' 'coef.evmSim.R' 'coefficients.evm.R'\n'coefficients.migpd.R' 'constructObject.R' 'copulas.R' 'cv.R'\n'degp3.R' 'dgev.R' 'dgpd.R' 'efficient.closures.R' 'egp3.R'\n'egp3RangeFit.R' 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"makeReferenceMarginalDistribution", "title": "Provide full marginal reference distribution for for maringal transformation", "topics": [ "makeReferenceMarginalDistribution" ] }, { "page": "MCS", "title": "Multivariate conditional Spearman's rho", "topics": [ "bootMCS", "ggplot.bootMCS", "ggplot.MCS", "MCS", "plot.bootMCS", "plot.MCS", "print.bootMCS", "print.MCS", "print.summary.bootMCS", "summary.bootMCS" ] }, { "page": "mexDependence", "title": "Estimate the dependence parameters in a conditional multivariate extreme values model", "topics": [ "mexDependence" ] }, { "page": "mexMonteCarlo", "title": "Simulation from dependence models", "topics": [ "mexMonteCarlo" ] }, { "page": "mexRangeFit", "title": "Estimate dependence parameters in a conditional multivariate extreme values model over a range of thresholds.", "topics": [ "mexRangeFit" ] }, { "page": "migpdCoefs", "title": "Change values of parameters in a migpd object", "topics": [ "migpdCoefs" ] }, { "page": "mrl", "title": 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