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Convolution is a function-valued operation on two functions $f$ and $g$: $\int _{-\infty }^{\infty }f(\tau )g(t-\tau )d\tau$. Often used for obtaining the density of a sum of independent random variables. This tag should also be used for the inverse operation of deconvolution. DO NOT use this tag for convolutional neural networks.

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Assume that I have two discrete random variables $X$ and $Y$. $X ∈ \{1,3,3,5,7,7,7,9,9,9,9,9\}$ and $Y ∈ \{5,5,9,9,10,12,13\}$ Where their empirical CDFs are given as: $F_x(1) = 0.0833, F_x(3) = …
asked May 15 by Levent Bekdemir
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I'm currently reading a paper which mentions supremal and infimal convolutions. As I understood, they are upper and lower bounds for a joint distribution. One of the formulas in that paper is as foll …
asked May 16 by Levent Bekdemir
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I'm trying to calculate sum of 2 random variables by using Copula Theory in R or Matlab. However, I have very limited knowledge about probability. Actually I read a lot of theoretical information abou …
asked Apr 14 by Levent Bekdemir