# Re: [R] Fitdistr and MLE for parameter lambda of Poisson distribution

From: Gregor Gorjanc <gregor.gorjanc_at_bfro.uni-lj.si>
Date: Tue 14 Feb 2006 - 19:57:48 EST

Bernardo Rangel tura wrote:

> At 09:35 AM 2/10/2006, Gregor Gorjanc wrote:
>


>> Hello!
>>
>> I would like to get MLE for parameter lambda of Poisson distribution. I
>> can use fitdistr() for this. After looking a bit into the code of this
>> function I can see that value for lambda and its standard error is
>> estimated via
>>
>> estimate <- mean(x)
>> sds <- sqrt(estimate/n)
>>
>> Is this MLE? With my poor math/stat knowledge I thought that MLE for
>> Poisson parameter is (in mixture of LaTeX code)
>>
>> l(\lambda|x) \propto \sum^n_{i=1}(-\lambda + x_iln(\lambda)).
>>
>> Is this really equal to (\sum^n_{i=1} x_i) / n
>>
>> --
>> Lep pozdrav / With regards,
>> Gregor Gorjanc
>
>
> Gregor,
>
> If I understood your LaTeX You is rigth.
>
> If you don´t know have a command wich make this for you:  fitdistr()
>
> Look:
>
>


>> d<- rpois(50,5)
>> d
>  [1]  6  4  6  4  5  5  4 11  7  5  7  3  5 10  4  9  4  2  4  5  4  4
> 9  3 10
> [26]  4  3  9  6  7  5  4  2  7  3  6  7  8  6  6  3  3  3  2  5  4  3
> 8  5  7


>> library(MASS)
>> fitdistr(d,"Poisson")
>     lambda
>   5.3200000
>  (0.3261901)



Thanks for this, but I have already said in the first mail, that fitdistr can help me with this. I was just "surprised" or knowledge undernourished, that there is closed form solution for this. Look into the source of fitdistr.

--
Lep pozdrav / With regards,
Gregor Gorjanc

----------------------------------------------------------------------
University of Ljubljana     PhD student
Biotechnical Faculty
Zootechnical Department     URI: http://www.bfro.uni-lj.si/MR/ggorjan
Groblje 3                   mail: gregor.gorjanc <at> bfro.uni-lj.si

SI-1230 Domzale             tel: +386 (0)1 72 17 861
Slovenia, Europe            fax: +386 (0)1 72 17 888

----------------------------------------------------------------------
"One must learn by doing the thing; for though you think you know it,
you have no certainty until you try." Sophocles ~ 450 B.C.

______________________________________________
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help