INFT 972/CSI 972 Mathematical Statistics I
(3:3:0).
Prerequisite: STAT 652 or equivalent. Focuses on the theory of estimation.
The principles of estimation are explored including the method of moments,
least squares, maximum likelihood, and maximum entropy methods. The methods
of minimum variance unbiased estimation are covered in detail. Topics
include sufficiency and completeness of statistics, Fisher information,
Cramer-Rao bounds, Bhattacharyya bounds, asymptotic consistency and
distributions, statistical decision theory, minimax and Bayesian decision
rules, and applications to engineering and scientific problems.
Taught by E. Wegman, M. Habib, J. Miller
Syllabus Available from E. Wegman, M. Habib