[R] poisson fit for histogram

[Prof Brian Ripley]

What does fit.dist do that fitdistr (MASS) does not in this context?  (It 
plots, but that is very easy to do in base R.  However, to see if a 
Poisson fits you need a test of goodness-of-fit.)

BTW, `decompress and store the files in your "library" folder' is on no OS 
(you did not mention one but Thomas did) the way to install a package. 
Even on Windows (where it might just work) there are simpler and better 
ways to do it, like using a menu.  Note that Lindsey does not provide 
pre-compiled packages for MacOS X, the platform Thomas is using (and as 
they use Fortran, people have reported that they are tricky to install on 
MacOS X), and your recipe is `seriously' misleading there.

On Fri, 22 Jul 2005, Francisco J. Zagmutt wrote:

> I would first reccomend you to update your version of R.  Then download the
> libraries rmutil and gnlm from Jim Lindsey at
> http://www.luc.ac.be/~jlindsey/rcode.html decompress and store the files in
> your "library" folder.   Sorry but you will have to donwload a package
> unless you seriously want to re-invent the wheel.
> Finally try
> library(gnlm)
> ?fit.dist()
>
> Cheers
>
> Francisco
>
>
>> From: Thomas Isenbarger <isen at plantpath.wisc.edu>
>> To: r-help at stat.math.ethz.ch
>> Subject: [R] poisson fit for histogram
>> Date: Wed, 20 Jul 2005 10:40:51 -0500
>>
>> I haven't been an R lister for a bit, but I hope to enlist someone's
>> help here.  I think this is a simple question, so I hope the answer
>> is not much trouble.  Can you please respond directly to this email
>> address in addition to the list (if responding to the list is
>> warranted)?
>>
>> I have a histogram and I want to see if the data fit a Poisson
>> distribution.  How do I do this?  It is preferable if it could be
>> done without having to install any or many packages.
>>
>> I use R Version 1.12 (1622) on OS X
>>
>> Thank-you very much,
>> Tom Isenbarger


-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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