Expectation of the Maximum Order Statistic of a Power Law Distribution
Didn’t know calculating expectation would take this long… Consider $n$ i.i.d. random variables $X_i$ drawn from Power Law distribution with support lowerbound $x_\text{min} = 1$ and the shape parameter $\alpha > 2$—in other words, the pdf of $X_i$ being $$ f_{X_i}(x) = (\alpha - 1) x^{-\alpha }, $$ and $$ F_{X_i}(x) =1 - x^{-(\alpha - 1)} \quad \text{ for }x \ge 1. $$ Btw, for the heavy-tailed distribution family, it can be more comfortable (and general) to understand random variable $X$ as $$ \Pr[X > x] \sim x^{-\alpha}....