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Re: st: Re: st: Searching for Kullback–Leibler divergence


From   "Michael C. Morrison" <[email protected]>
To   [email protected]
Subject   Re: st: Re: st: Searching for Kullback–Leibler divergence
Date   Sun, 09 May 2010 13:21:31 -0500

Thanks for your help. I'm relying heavily on Handcock and Morris (1999) Relative Distribution Methods in the Social Sciences.

If you look at this article

http://www.stat.psu.edu/reports/1997/tr9702.pdf

the equation that I eventually need to satisfy is 4.1 but getting there is the problem. I'm not a programmer.

R code is found here, http://www.csss.washington.edu/Papers/wp27.pdf (by Handcock and Aldrich), specifically section 5, with summary in section 6.

Perhaps an ado would help the community of researchers utilizing this powerful tool, albeit it's not a perfect tool (it's not symmetric, as a change in the arguments result in different outcomes.)?

Mike


On 5/9/2010 12:32 PM, Tirthankar Chakravarty wrote:
Michael,

That, I think, is a slightly harder problem. See here and the references within:
http://www.tsc.uc3m.es/~fernando/bare_conf3.pdf

Most of these references ([21], [12], [5], [22], [13], [18]) are
recent and fairly involved. If you have an algorithm in mind that
would be very helpful in answering your question/supplying you with
code. Eqn (4) in the link above is fairly easily programmable.

However, it would be much easier if I could see what you have in mind
in situ, so a reference to an application would be great.

T

2010/5/9 Michael C. Morrison<[email protected]>
Tirthankar Chakravarty advised that I look into -multigof- for the Kullback–Leiber divergence. Thanks for the response but -multigof- is not what I'm looking for.

Kullback–Leiber divergence is sometimes referred to as 'relative entropy' or 'cross entropy'. The Kullback–Leiber divergence that I need summarizes the effect of location and shape changes on the overall relative distribution involving two continuous distributions. The Kullback–Leiber divergence has a simple interpretation in terms of the relative distribution, and it is decomposable into the location, shape and other components.

I have - reldist-. It  does a great job in plotting relative&  cumulative pdfs, location/shape shift changes, polarization coefficients, but it doesn't provide a measure of the overall distributional difference between two distributions. That's where the The Kullback–Leiber divergence comes to the rescue. The advantage of the Kullback–Leiber divergence is that it is decomposable.

Hope this clarifies what I'm searching for.

Mike
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--
To every ω-consistent recursive class κ of formulae there correspond
recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
belongs to Flg(κ) (where v is the free variable of r).

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