Cramer-Rao bound

(1.1 hours to learn)


The Cramer-Rao bound gives the minimum possible variance of an unbiased estimator of the parameters of a probability distribution. It is used to prove the asymptotic efficiency of the maximum likelihood estimator.


This concept has the prerequisites:


  • Prove the Cramer-Rao theorem, which bounds the variance of any unbiased estimator of model parameters.
  • Use the result to compute the asymptotic relative efficiency of an estimator.

Core resources (read/watch one of the following)


See also