R help - Nov 2013 - Comparison of two weibull distributions

Hello,

How can I do a test of two weibull distributions?
I have two weibull distribution sets from two wind datasets in order to
check whether they are same.
I thought 2 sample t-test would be applicable but I couldn't find any ways
to do that on the Internet.
Does anyone know what type of test is applicable to my purpose? and what R
function can you recommend?
Plus, if it turned out that there is a difference between the two datasets,
can I just fit a linear line between the datasets? 

Kind Regards,

Kangmin.



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kmmoon100 <k.moon <at> student.unimelb.edu.au> writes:
> 
> Hello,
> 
> How can I do a test of two weibull distributions?
> I have two weibull distribution sets from two wind datasets in order to
> check whether they are same.
> I thought 2 sample t-test would be applicable but I couldn't find any
ways
> to do that on the Internet.
> Does anyone know what type of test is applicable to my purpose? and what R
> function can you recommend?
> Plus, if it turned out that there is a difference between the two datasets,
> can I just fit a linear line between the datasets? 
> 
> Kind Regards,
> 
> Kangmin.
  (1) Fit a single model to the combined (pooled data) (e.g. with
MASS::fitdistr()); (2) fit separate models to the individual data
sets; (3) compare the log-likelihood of the pooled model to the
sum of the log-likelihoods of the separate models.  According to
the likelihood ratio test, the p-value of the differences is:

  pchisq(2*(logLik_sum-logLik_pooled),df=2,lower.tail=FALSE)

(2 df because the separate models have a total of 4 parameters,
2 greater than the pooled model)