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What is Linear MMSE Estimation Explained about?

This document summarizes linear minimum mean squared error (MMSE) estimation of random variables. It states that the linear MMSE estimator of a random variable X given another random variable Y is of the form X̂L = aY + b, where a and b are chosen to minimize the mean squared error between X and X̂L. The document provides a theorem that shows a* = Cov(X,Y)/Var(Y) and b* = EX - a*EY minimize the MSE. It further states that the linear MMSE estimator satisfies the orthogonality principle that the estimation er

Author

bossishere

Language

EN