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In probability theory, an empirical measure is a random measure arising from a particular realization of a sequence of random variables. The precise definition is found below. Empirical measures are relevant to mathematical statistics.
The motivation for studying empirical measures is that it is often impossible to know the true underlying probability measure P {\displaystyle P}. We collect observations X 1 , X 2 , … , X n {\displaystyle X_{1},X_{2},\dots ,X_{n}} and compute relative frequencies. We can estimate P {\displaystyle P} , or a related distribution function F {\displaystyle F} by means of the empirical measure or empirical distribution function, respectively. These are uniformly good estimates under certain conditions. Theorems in the area of empirical processes provide rates of this convergence.