search for: gpdfit

...truncated sample. >From an empirical sample I've estimated a generalized pareto distribution parameters (xi, beta, threshold) (I've used fExtremes pkg). I'm in doubt on what of the following command is the most appropriate: Let: x<-sample t<-threshold xt<-x[x>t] xihat<-gpdFit(x, threshold=t, type = "pwm")$par.ests[1] betahat<-gpdFit(x, threshold=t, type = "pwm")$par.ests[2] (1) ks.test(xt,"pgpd",list(xi=xihat,beta=betahat),H=t,estfun = "as.list(gpdFit(x, 0)$par.ests)", tol = 1e-02) (2) ks.test(xt,"pgpd",list(xi=xihat,...

...Extremes: data(danish) xmpExtremes("\nStart: Simulate a GPD Distributed Sample > ") x = gpdSim(model = list(shape = 0.25, location = 0, scale = 1), n = 1000) Error in rgpd(n = n, xi = model$shape, mu = model$location, beta = model$scale) : unused argument(s) (mu ...) fit = gpdFit(danish, threshold = 10, type = "mle") > par(mfrow = c(1, 1)) > gpdtailPlot(fit, main = "Danish Fire: GPD Tail Estimate", col = "steelblue4") Error in as.numeric(gpd.obj$upper.exceed) : argument "gpd.obj" is missing, with no default

Dear all, I've recently switched from EViews to R with RMetrics/fSeries (newest version of july 10) for my analysis because of the much bigger flexibility it offers. So far my experiences had been great -prior I had already worked extensively with S-Plus so was already kind of familiar with the language- until I got to the fSeries package. My problem with the documentation of fSeries is that