[R] fitdistr, mle's and gamma distribution

[Spencer Graves]

      Are you interested in turning that into a monitor, processing each 
day's data sequentially or even each entry as it arrived?  If yes, you 
may wish to evaluate the "Foundations of Monitoring" documents 
downloadable from "www.prodsyse.com".  If you have any questions about 
that, I might be able to help. 

      hope this helps.  spencer graves

Lourens Olivier Walters wrote:

>Thanks for the help, the wrapper function was very useful. I managed to
>solve the problem using Spencer Graves' suggestion. I am analyzing the
>interarrival times between HTTP packets on a campus network. The dataset
>actually has more than 14 Million entries! It represents the traffic
>generated by approximately 3000 users browsing the web for 30 days. I
>have to be careful to always remove unused objects from my workspace,
>but otherwise I have so far managed to cope with 512Mb of memory on a
>Pentium 600Mhz. 
>
>Lourens
>
>On Tue, 2003-09-30 at 23:25, Ben Bolker wrote:
>  
>
>>  PS.  11 MILLION entries??
>>
>>On Tue, 30 Sep 2003, Ben Bolker wrote:
>>
>>    
>>
>>>  Spencer Graves's suggestion of using shape and scale parameters on a log 
>>>scale is a good one.
>>>
>>>  To do specifically what you want (check values for which the objective 
>>>function is called and see what happens) you can do the following 
>>>(untested!), which makes a local copy of dgamma that you can mess with:
>>>
>>>dgamma.old <- dgamma
>>>dgamma <- function(x,shape,rate,...) {
>>>   d <- dgamma.old(x,shape,rate,...)
>>>   cat(shape,rate,d,"\n")
>>>   return(d)
>>>}
>>>      
>>>
>
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