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"Clay S. Turner" <[EMAIL PROTECTED]> wrote in message news:[EMAIL PROTECTED] > Hello Walala, > > How big is your sample size? If you grab only100 samples, you wouldn't > expect it to exactly fit the generating distribution. Can you grab 1,000,000 > samples? If still it doesn't fit, then suspect your generating dist. is > different from a Laplacian. You can look into bootstrapping methods to get > an estimate of the dist. > > Clay > > > > > "walala" <[EMAIL PROTECTED]> wrote in message > news:[EMAIL PROTECTED] > > Dear all, > > > > 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... :=) > > > > Thanks a lot, > > > > -Walala > > > > > > Dear Clay, 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!)
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