search for: fitgpd

...atrix with element like "Numeric,2" ... I guess they are just the values for "parab", and we can not even see the two parameters in parab. parameter <- function(v) { v1 <- v[v>mean(v)+0.5*sd(v)] v2 <- v[v<mean(v)-0.5*sd(v)] alpha=min(v1) beta=max(v2) para <- fitgpd(v1,alpha, method="pwmu")$param parab <- fitgpd((-v2), (-beta), method="pwmu")$param v1.fit <- qgpd(ppoints(v1, a=0.5), alpha, para[1], para[2]) v2.fit <- qgpd(ppoints((-v2), a=0.5), (-beta), para[1], para[2]) alpha beta para parab } tapply(variable, list(a, b),param...

Hi, I have a problem in fitting GPD distribution. i generate random numbers from gpd distribution from specific parameters using pot packege then i used fitgpd function to estimete the parameters.The estimated parameters are not matched with the given parameters i.e.from which i generate random numbers.I think estimated parameters should be matched with the given parameters.Also suggest me another good packege for GPD. for e.g. k2<-rgpd(100,loc=10000...

Up to now, I have recognized problems with "gpd(..)", the function from the package "evir" I think that all these functions that estimate the parameters xi, beta for the GPD by given threshold mu use the function "optim(..)" ( gpd, fitgpd, ...) "Error" example: data1 <- rgpd(1000, xi= -1.5, mu=1000, beta=100) so the created poinnts take place in about (1000, 1070). Now I want to estimate xi and beta by given threshold =1060, out <- gpd(data1, threshold=1060) and this causes an error in "optim". My...

I would like to fit a Pareto Distribution and I am using the following codes. I thought the fitted (fit1) should be the fitted value for the data, is it correct? As the result of the "fitted" turns out to be a single value for all. fit=vglm(ycf1 ~ 1, pareto1(location=alpha), trace=TRUE, crit="c") fitted(fit) The result is fitted(fit) [,1] [1,] 0.07752694