R help - Jun 2010 - Fitting Gamma distribution

I'm looking for goodness of fit tests for gamma distributions with large
data
sizes and for different data. 
I have a matrix with around 4.000 data values in it and i have fitted a
gamma distribution with "fitdistr".

You can see the example:
 
> fitdistr(corpo,"gamma",lower=0.001)
  Errore in optim(x = c(5000, 5000, 5000, 5000, 5000, 5000, 5000, 5000,
5000,  : 
  non-finite finite-difference value [2]

The problem is the optimization for the test with different data and for the
size larger than 516 data. 

in summary 
-is there a gamma goodness of fit test that doesnt depend on the sample
size? 
-is there a way of using qqplot for gamma distributions, if so how would you
calculate it from a matrix of data values? 

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You can use rgamma to get a gamma distribution for use in qqplot, eg :

x <-rchisq(100,2)
y<- fitdistr(x,"gamma")

qqplot(rgamma(100,y$estimate[1],y$estimate[2], x)

Cheers
Joris



On Wed, Jun 16, 2010 at 9:40 AM, Marcosco01
<marco.scortichini at bancamarche.it> wrote:
>
> I'm looking for goodness of fit tests for gamma distributions with
large data
> sizes and for different data.
> I have a matrix with around 4.000 data values in it and i have fitted a
> gamma distribution with "fitdistr".
>
> You can see the example:
>
>> fitdistr(corpo,"gamma",lower=0.001)
>
> ?Errore in optim(x = c(5000, 5000, 5000, 5000, 5000, 5000, 5000, 5000,
> 5000, ?:
> ?non-finite finite-difference value [2]
>
> The problem is the optimization for the test with different data and for
the
> size larger than 516 data.
>
> in summary
> -is there a gamma goodness of fit test that doesnt depend on the sample
> size?
> -is there a way of using qqplot for gamma distributions, if so how would
you
> calculate it from a matrix of data values?
>
> --
> View this message in context:
http://r.789695.n4.nabble.com/Fitting-Gamma-distribution-tp2257014p2257014.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>


-- 
Joris Meys
Statistical consultant

Ghent University
Faculty of Bioscience Engineering
Department of Applied mathematics, biometrics and process control

tel : +32 9 264 59 87
Joris.Meys at Ugent.be
-------------------------------
Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php

I'm looking for goodness of fit tests for gamma distributions with large
data
sizes and for different data. 
I have a matrix with around 4.000 data values about losses and there is a
heavy right-tail in it. 
I have fitted a gamma distribution with "fitdistr". 

You can see the example: 

fitdistr(corpo,"gamma",lower=0.001) 

Errore in optim(x = c(5000, 5000, 5000, 5000, 5000, 5000, 5000, 5000, 
5000,  : non-finite finite-difference value [2] 

The problem is the optimization for the test with different data.

In summary 
- how to estimate the parameters? 
- is there another way to estimate the gamma parameters that doesnt depend
on the sample size? 


-- 
View this message in context:
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Sent from the R help mailing list archive at Nabble.com.