Course - Probability Theory and Asymptotic Techniques - MA8704
Probability Theory and Asymptotic Techniques
About
About the course
Course content
The course is taught only if a sufficient number of students register, next time Fall 2010. If too few students register, then the course is only given as a guided self study.
The course gives a broad introduction to classical probability theory and asymptotic techniques towards applications in statistics. Together with course MA8701 (DIF5921) General statistical methods it provides a theoretical basis for PhD students in statistics. The contents include basic probability theory, convergence of sequences of random variables, characteristic functions, classical limit theorems, prediction and conditional expectation, asymptotic results for maximum likelihood estimators and likelihood ratio tests, asymptotic expansions, Laplace-, Edgeworth- and saddelpoint approximations.
Learning methods and activities
Lectures, alternatively guided self-study.
Recommended previous knowledge
The course requires good statistical background, such as TMA4295 (SIF5084) Statistical inference or equivalent.
Course materials
Will be announced at the start of the course.
Subject areas
- Statistics