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 Apr13 revised Infinite self-convolution for a function added 36 characters in body Apr13 revised Infinite self-convolution for a function added 172 characters in body Apr13 comment Infinite self-convolution for a function @StefanSmith: Yeah, I am also getting contradictory results. It is not easy to manage this thing here... Furthermore, nobody asked me to solve this specific problem, actually it is just something that I need to do in order to achieve another target. Apr13 revised Infinite self-convolution for a function added 58 characters in body Apr13 comment Infinite self-convolution for a function Yes! I thought it was the same right? Apr12 comment Infinite self-convolution for a function Variance increases everytime... and it seems not reaching a stable value... Apr12 revised Infinite self-convolution for a function Added picture Apr12 asked Infinite self-convolution for a function Mar31 asked Proof about how to get a uniform random variable from a generic one Mar20 revised Problems getting transformation function from source and destination random variables knowledge when handling the discrete case Grammar check Mar20 comment Problems getting transformation function from source and destination random variables knowledge when handling the discrete case Thankyou user65384 for your answer, but I am afraid to say that you did not get the point. I do not want to know how to get $F_Y(y)$, in my case I suppose I already have it. In your example you use $g(\cdot) = ln(\cdot)$ but in my question I pointed clear that $g$ must be $g(\cdot) =F_Y^{-1}(F_X(\cdot))$. In particular I need to consider the case where $F_Y(y)$ is a stair function that, so, cannot be inverted! Mar19 asked Problems getting transformation function from source and destination random variables knowledge when handling the discrete case Mar19 comment Deriving the transformation function of a random variable from the original and the final distributions Just a question, how can I make the transformation when X and Y are discrete? $F_Y^{-1}(y)$ cannot be done... Mar17 accepted Deriving the transformation function of a random variable from the original and the final distributions Mar17 asked Deriving the transformation function of a random variable from the original and the final distributions Feb18 comment Deriving the process of successfully consumed requests from the process of request-producers and the process of request-consumers At the moment I am thinking how to re-write the question in a better way... Need some time sorry... you are right btw... Feb18 comment Deriving the process of successfully consumed requests from the process of request-producers and the process of request-consumers This is what I am trying to understand... I provided some initial data, but I am trying to device a way to get this thing done... In my question I just wanted to know about a possible approach using the two quantities I introduced (say the two probabilities). I am aware that the question is getting a little vague... I'll try to edit it it... Feb18 comment Deriving the process of successfully consumed requests from the process of request-producers and the process of request-consumers @joriki: It is one of the things I am asking as well... Feb18 revised Deriving the process of successfully consumed requests from the process of request-producers and the process of request-consumers added 671 characters in body Feb17 comment Deriving the process of successfully consumed requests from the process of request-producers and the process of request-consumers I had a feeling... But I cannot figure out how to adapt a death-birth model to this scenario. Btw, gonna check it out, thank you very much!