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Hello, I can`t figure out how can increase the velocity of the fitting data by nls. I have a long data .csv I want to read evry time the first colunm to the other colunm and analisy with thata tools setwd("C:/dati") a<-read.table("Normalizzazione.csv", sep=",", dec=".", header=F) for (i in 1:dim(a[[2]]]) { #preparazione dati da analizzare

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=100000,scale=229678.21 ,sh...