[R] Which distribution best fits the data?

[Peng Jiang]

  I agree with Ben  . without providing any information of the data, we
   cannot make inference on the distribution itself.
   actually density estimation is a tough problem( and classical ). Of  
course,
  there are methods like GMM or some other method based on statistical  
learning,
  however, they make assumptions and only do the approximation.

I hope anyone can explain more on this topic using more R specific  
language.


On 2008-6-30, at 下午7:50, Ben Bolker wrote:

> Jenny Barnes <jmb <at> mssl.ucl.ac.uk> writes:
>
>>
>> Dear R-help community,
>>
>> Does anybody know of a stats function in R that tells you which
>> distribution best fits your data? I have tried look through the  
>> archives
>> but have only found functions that tell you if it's normal or log  
>> etc.
>> specifically - I am looking for a function that tells you (given a
>> timeseries) what the distribution is.
>>
>> Any help/advice will be greatly appreciated,
>>
>> All the best,
>>
>> Jenny Barnes
>>
>> jmb <at> mssl.ucl.ac.uk
>
>   The problem is that it's not generally a good
> idea to data-dredge in this way. Your best bet is
> to think about the characteristics of the
> data (discrete or continuous, non-negative or real,
> symmetric or skewed) and try to narrow it down to
> a few distributions -- then you can use fitdistr()
> (from the MASS package) or something similar
> to compare among them.
>
>  If you say a little bit more about what
> you're trying to do with the data you might
> get some more specific advice.
>
>  Ben Bolker
>
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-----------------------------------------------
Peng Jiang 江鹏 ,Ph.D. Candidate
Antai College of Economics & Management
安泰经济管理学院
Department of Mathematics
数学系
Shanghai Jiaotong University (Minhang Campus)
800 Dongchuan Road
200240 Shanghai
P. R. China