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Probability : joint density function of 3 Normal Distributions |
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| Nov15-06, 11:55 AM | #1 |
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Probability : joint density function of 3 Normal Distributions
X1, X2, X3 are independent gaussian random variables.
Y1 = X1+X2+X3 Y2 = X1-X2 Y3 = X2-X3 are given. What is the joint pdf of Y1,Y2 and Y3 ? |
| Nov18-06, 10:18 AM | #2 |
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What are you confused about in this problem?
You have to show what work you've done in order to get help. And if you've made no progress whatesoever, just write what you don't understand about the problem. |
| Nov22-06, 05:21 PM | #3 |
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| Jun10-08, 07:52 AM | #4 |
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Probability : joint density function of 3 Normal Distributions
Dear,
If you are always watching the post. the pdf of Y1 is the convolution of the three pdfs of the three random variables (X1, X2 and X3). for Y2 and Y3, if the random variables are gaussian and centered (mean = 0) then pdf(X) = pdf(-X) and thus for pdf(Y2) = convolution of pdf(X1) and pdf(X2) while pdf(Y3) = convolution of pdf(X2) and pdf(X3). Actually, I address you to the great book of Papoulis where you can find (for sure) the answer to your wondering . Cheers Manar |
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