## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----package, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE------ library(ReturnCurves) ## ----data, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE--------- data(airdata) ## ----margdata, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE----- # qmarg and constrainedshape set to the default values expdata <- margtransf(data = airdata, qmarg = rep(0.95, 2), constrainedshape = T) # attributes of the S4 object str(expdata) # head of the data on standard exponential margins head(expdata@dataexp) ## ----plotsmarghist, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE, fig.align = 'center'---- plot(expdata, which = "hist") ## ----plotsmargts, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE, fig.align = 'center'---- plot(expdata, which = "ts") ## ----plotsmargjoint, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE, fig.align = 'center', fig.height = 2.5---- plot(expdata, which = "joint") ## ----plotsmargall, echo=TRUE, fig.align='center', fig.height = 8, message=FALSE, warning=FALSE, paged.print=FALSE---- plot(expdata, which = "all") # or just plot(expdata) ## ----marggpd, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE------ # nboot and alpha are set to the default values # blocksize is set to 10 to account for temporal dependence uncgpd <- marggpd(margdata = expdata, blocksize = 10, nboot = 250, alpha = 0.05) # attributes of the S4 object str(uncgpd) # head of the list elements of slot marggpd for variable X head(uncgpd@marggpd$model[[1]]) head(uncgpd@marggpd$empirical[[1]]) head(uncgpd@marggpd$lower[[1]]) head(uncgpd@marggpd$upper[[1]]) ## ----plotsmarggpd, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE, fig.align = 'center', fig.width = 6.5, fig.height = 2.5---- plot(uncgpd) ## ----adfest, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE------- # Estimation using Hill estimator without conditional extremes parameters whill <- seq(0, 1, by = 0.001) ## q and constrained are set to the default values here lambdah <- adf_est(margdata = expdata, w = whill, method = "hill", q = 0.95, constrained = F) # Estimation using Hill estimator with conditional extremes parameters ## q and qalphas are set to the default values lambdah2 <- adf_est(margdata = expdata, w = whill, method = "hill", q = 0.95, qalphas = rep(0.95, 2), constrained = T) # Estimation using CL method without conditional extremes parameters ## w, q and constrained are set to the default values here lambdacl <- adf_est(margdata = expdata, w = seq(0, 1, by = 0.01), method = "cl", q = 0.95, constrained = F) # Estimation using CL method with conditional extremes parameters ## w, q and qalphas are set to the default values lambdacl2 <- adf_est(margdata = expdata, w = seq(0, 1, by = 0.01), method = "cl", q = 0.95, qalphas = rep(0.95, 2), constrained = T) # attributes of the S4 object str(lambdah) # head of the vector with adf estimates for the first estimator head(lambdah@adf) ## ----plotsadfest, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE, fig.width = 5, fig.height = 2.5, fig.align = 'center'---- # plot of the ADF estimation based on the unconstrained Hill estimator plot(lambdah) ## ----adfgof, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE------- # Goodness of fit of the adf for twp rays w rays <- c(0.25, 0.75) ## nboot and alpha are set to the default values ## blocksize is set to 10 to account for temporal dependence gofh <- sapply(rays, adf_gof, adf = lambdah, blocksize = 10, nboot = 250, alpha = 0.05) # attributes of the S4 object str(gofh[[1]]) # head of the list elements of slot gof head(gofh[[1]]@gof$model) head(gofh[[1]]@gof$empirical) head(gofh[[1]]@gof$lower) head(gofh[[1]]@gof$upper) ## ----plotsadfgof, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE, fig.align = 'center', fig.width = 6.5, fig.height = 2.5---- library(gridExtra) grid.arrange(plot(gofh[[1]]), plot(gofh[[2]]), ncol = 2) ## ----rcest, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE-------- n <- dim(airdata)[1] prob <- 10/n # Estimation using Hill estimator without conditional extremes parameters whill <- seq(0, 1, by = 0.001) ## q and constrained are set to the default values here rch <- rc_est(margdata = expdata, w = whill, p = prob, method = "hill", q = 0.95, constrained = F) # Estimation using Hill estimator with conditional extremes parameters ## q and qalphas are set to the default values rch2 <- rc_est(margdata = expdata, w = whill, p = prob, method = "hill", q = 0.95, qalphas = rep(0.95, 2), constrained = T) # Estimation using CL method without conditional extremes parameters ## w, q and constrained are set to the default values here rccl <- rc_est(margdata = expdata, w = seq(0, 1, by = 0.01), p = prob, method = "cl", q = 0.95, constrained = F) # Estimation using CL method with conditional extremes parameters ## w, q and qalphas are set to the default values rccl2 <- rc_est(margdata = expdata, w = seq(0, 1, by = 0.01), p = prob, method = "cl", q = 0.95, qalphas = rep(0.95, 2), constrained = T) # attributes of the S4 object str(rch) # head of the vector with adf estimates for the first estimator head(rch@rc) ## ----plotsrcest, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE, fig.width = 5, fig.height = 3, fig.align = 'center'---- # plot of the ADF estimation based on the unconstrained Hill estimator plot(rch) ## ----rcunc, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE-------- # nangles and alpha set to default # nboot set to 50 for simplicity # blocksize is set to 10 to account for temporal dependence rch_unc <- rc_unc(rch, blocksize = 10, nboot = 50, nangles = 150, alpha = 0.05) # attributes of the S4 object str(rch_unc) # head of the list elements of slot unc head(rch_unc@unc$median) head(rch_unc@unc$mean) head(rch_unc@unc$lower) head(rch_unc@unc$upper) ## ----plotsrcunc, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE, fig.align = 'center', fig.height=6,fig.width=8---- library(gridExtra) grid.arrange(plot(rch_unc, which = "rc"), plot(rch_unc, which = "median"), plot(rch_unc, which = "mean"), plot(rch_unc, which = "all"), nrow = 2) ## ----rcgof, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE-------- # nboot, nangles and alpha set to default # blocksize is set to 10 to account for temporal dependence rch_gof <- rc_gof(rch, blocksize = 10, nboot = 250, nangles = 150, alpha = 0.05) # attributes of the S4 object str(rch_gof) # head of the list elements of slot gof head(rch_gof@gof$median) head(rch_gof@gof$lower) head(rch_gof@gof$upper) ## ----plotsrcgof, echo=TRUE, message=FALSE, warning=FALSE, paged.print=FALSE, fig.align = 'center', fig.height = 3---- plot(rch_gof)