Hello,
Why quantile(train, 0.9) ? If you use quantile(train) it seems to fit
the data much better. You haven't posted a data example so I've made up one.
library(eva) # needed for rgpd()
library(extRemes)
set.seed(1)
train <- rgpd(1e3, scale = 0.9, shape = -0.4)
thresh90 <- quantile(train)
Let the train be the data set consisting of numbers that I need to fit.
Code is as follows:
library(extRemes)
thresh90 <- quantile(train, 0.90)
model<-fevd(train,threshold =thresh90,type="GP")
Model returns the following :
Negative Log-Likelihood Value: 317.7561
Estimated parameters:
scal
Hello,
Please provide us with a reproducible example. A data exampla would be
nice and some working code, the code you are using to fit the data.
Rui Barradas
Em 27-11-2016 15:04, TicoR escreveu:
I am trying to fit some data using Generalized Pareto Distribution in R
using extRemes package(h
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