Re: (statistics)how to make date more like Laplacian distribution?

"John D'Errico" <[EMAIL PROTECTED]> wrote in message
news:[EMAIL PROTECTED]
> In article <[EMAIL PROTECTED]>,
>  "walala" <[EMAIL PROTECTED]> wrote:
>
> > If I already know a prior that my data distribution should follow the
shape
> > of Laplacian distribution... the data obtained from measurement is of
course
> > a little off(not very symmtrical), how can I make the measured data more
> > Laplacian distribution like(make it at least a little more symmtrical)?
> >
> > Can anybody give me an example or detailed explanation? I am kind of
afraid
> > of statistics... :=)
>
>
> Lets see if I understand. Your data does not follow
> your prior beliefs. Therefore the data is wrong, and
> you want to know how to modify said data so that it
> does exactly what you want. This makes sense - in a
> very distorted way.
>
> Why did you bother with measuring that blasted data
> in the first place? You have already decided the
> result. Measurements just get in the way.
>
> Please start by reading the book "How to lie with
> Statistics". Then return to your data, and learn from
> it. Is it just random noise that has given your data
> this property you did not expect? Or is this an
> indication of a problem in your measurement? Perhaps
> it indicates something wrong with the theory? Perhaps
> another factor distorts the data? Maybe your sample
> is just too small!
>
> I can summarize the strong suggestions I give to my
> students who deal with data in three words:
>
> Plot - think - learn.
>
> Only after that do I tell them to do any actual
> modeling, or use their data in any way.
>
> HTH,
> John D'Errico
>
>
> -- 
> There are no questions "?" about my real address.
>
> The best material model of a cat is another, or
> preferably the same, cat.
> A. Rosenblueth, Philosophy of Science, 1945

Dear John,

Why people think I want to lie upon seeing my question? Oh, it's my problem
that I did not clearly present the background...

Here is the story: in deblocking of block DCT coded JPEG images, it was
known that the DCTed coefficients are Laplacian distributed... But now I am
looking at low bit rate JPEG images, so there are someking of artifacts...
in order to reconstruct the original images... many algorithms have been
devised... one possibility is to make the image coefficients more Laplcian
like...

So that came my question: how to make data more Laplican like...Please give
me some detailed explanation as I am not veteran in statistics...

Thanks a lot,

-Walala

(I am just a poor student, not lieing government agency, issurance company,
weapon dealer, lawyers, and politicians... so please help me!)