Likelihood function and likelihood principle, sufficiency, completeness of exponential families, Cramer-Rao lower bound, Lehmann-Scheffe Theorem, Rao-Blackwell Theorem, estimation methods, basic asymptotic theory, consistent asymptotic normal estimators (CAN), asymptotic properties of the maximum likelihood estimators, Bayesian estimation.
This course may not be repeated for credit.
Prerequisite(s)
- Statistics 323 or Mathematics 323; and Mathematics 353 or 367 or 381.
SyllabusSections
This course will be offered next in
Fall 2018.