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Functions of Random Variables Explained by Randy Sooknanan is a document available to read on EtoBox.

The document discusses functions of random variables. It defines a random variable Y as a function r(X) of another random variable X. To find the probability density function (p.d.f.) of Y, one first calculates the cumulative distribution function (c.d.f.) of Y and then takes the derivative. If r is monotonic, the inverse function r^-1 can be used to relate the c.d.f.s of X and Y. If X and Y are independent random variables, the p.d.f. of their sum Z is the convolution of the individual p.d.f.s. Examples ar

Author
Randy Sooknanan
Language
EN