Dear All,

 

I am trying to fit some data to a Pareto distribution and would like to
estimate the parameters with the fitting. I have come across some options so
far. Unfortunately I haven't managed to get any of them to make the right
fits (as is evident when I check with the goodness of fit). One such option
is:

 

library(VGAM)

b1 <- read.table(file("FitPareto_Values.txt", encoding="latin1"))

b2 <- as.vector(t((b1[2])))

fit = vglm(b2 ~ 1, pareto1, trace=TRUE)

 

With this code, R returns a coefficient for the intercept in the Pareto
distribution as (-1.434) and this doesn't make any practical sense for the
scenario that I am trying to model.

 

Could anyone tell me where I could be going wrong? Or could you suggest
alternative ways of fitting such data? Any help would be deeply appreciated!

 

Thanks in advance!


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