Perhaps a lot of us buy Stata because, once one user has programmed a
method properly, the other users will not have to do so, because the
package can be downloaded from SSC etc.
This is also an advantage of R (which scores on price compared to
Stata). However, most R users seem to agree that R doesn't have the
level of data-handling capabilities that we Stata users have become
accustomed to. I suspect (somebody correct me if I'm wrong) that this is
because the R community are mostly career methodologists, who are keen
to be the first to install a new method, but are not so keen to write
data-handling software to lighten the load of people with bosses,
deadlines and other workplace afflictions.
Roger
Roger Newson
Lecturer in Medical Statistics
Respiratory Epidemiology and Public Health Group
National Heart and Lung Institute
Imperial College London
Royal Brompton campus
Room 33, Emmanuel Kaye Building
1B Manresa Road
London SW3 6LR
UNITED KINGDOM
Tel: +44 (0)20 7352 8121 ext 3381
Fax: +44 (0)20 7351 8322
Email: [email protected]
Web page: www.imperial.ac.uk/nhli/r.newson/
Departmental Web page:
http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/pop
genetics/reph/
Opinions expressed are those of the author, not of the institution.
-----Original Message-----
From: [email protected]
[mailto:[email protected]] On Behalf Of Marcello
Pagano
Sent: 22 August 2007 18:33
To: [email protected]
Subject: Re: st: RE: Hypergeometric Distribution
Why buy Stata if you are expected to do all this for yourself?
m.p.
Nick Cox wrote:
> Apply -ln()-, -exp()- and -cond()- as needed.
>
> Nick
> [email protected]
>
> Marcello Pagano
>
>
>> Just concerned with the accuracy.
>>
>
>
>> Nick Cox wrote:
>>
>
>
>>> Roger's posting includes what I presume is an allusion to
>>> an -egen- function _ghyper.ado that I wrote in 1999.
>>>
>>> I withdrew this program as redundant some years ago,
>>> given that you can use something like
>>>
>>> comb(K, k) * comb(N - K, n - k) / comb(N, n)
>>>
>>> wherever you want. In context N, K, n, k may be
>>> variables, scalars or placeholders for numeric
>>> constants, or any mixture thereof.
>>>
>>> This might need a wrapper to yield zeros where
>>> appropriate, or it might need care whenever
>>> individual terms get very large, but otherwise
>>> does it raise any problems?
>>>
>>> Nick
>>> [email protected]
>>>
>>> Marcello Pagano
>>>
>>>
>>>
>>>> I looked at --ssizebi-- but it seems to be focused on power
>>>> and sample
>>>> sizes.
>>>>
>>>>
>>>
>>> Newson, Roger B wrote:
>>>
>>>
>>>
>>>>> Thanks to Marcello for telling us all about this
>>>>>
>> recently-published
>>
>>>>> algorithm, which looks very useful. A search on
>>>>>
>>>>> findit hypergeometric
>>>>>
>>>>> in Stata finds a single reference (to a SSC package), which was
>>>>> distributed as long ago as 1999. This suggests that the new
>>>>>
>>>>>
>>>> algorithm
>>>>
>>>>
>>>>> might be a good candidate for implementation in Mata by
>>>>>
>>>>>
>>>> Marcello, or by
>>>>
>>>>
>>>>> anybody else with the time and inclination to do so.
>>>>>
>>>>>
>>> Marcello Pagano
>>>
>>>
>>>
>>>> Does anyone have or know of Stata code to calculate the
>>>>
>> Hypergeometric
>>
>>>> Distribution accurately?
>>>>
>>>> See Journal of Discrete Algorithms , Volume 5 , Issue 2
>>>>
>> (June 2007)
>>
>>>> Pages: 341-347 for an article by Berkopec, HyperQuick
>>>>
>> algorithm for
>>
>>>> discrete hypergeometric distribution
>>>>
>>>>
>
<http://portal.acm.org/citation.cfm?id=1240586&coll=GUIDE&dl=GUIDE&CFID=
>
>>> 27443384&CFTOKEN=80678482>.
>>>
>
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>
*
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