Asymptotic Statistics A
Lecturer: Markus Pauly
Exercises taught by: Dennis Dobler
Time and Venue
|Lectures||Wed., from 8 to 10 a.m. in N24-131. Starting October 14.|
|Exercise||Thu., from 4 to 5 p.m. in He22, E18. Starting October 15.|
Oral Exams: During the week April 4 to 8, 2016.
|Prerequisites:||Suitable for masters students in "Mathematischer Biometrie", "Mathematik", "Wirtschaftsmathematik" or "Finance". Knowledge in measure theory and probability theory (including limit theorems) are required in advance.|
|Exam:||Once 40 per cent of all exercise points are achieved, an application for the exam is possible.|
Contents: Excerpts of the following topics are covered in Asymptotic Statistics A and B:
Many of the classical statistical inference procedures need specific and stringent distributional assumptions which are often not met in practice. In the course it is shown how the tools of asymptotic statistics may provide a way out. In particular, the construction of asymptotic estimates, confidence intervals and tests is studied covering topics such as asymptotic (relative) efficiency, likelihood-ratio statistics, nonparametric density estimation, rank tests, resampling (e.g. bootstrapping and permutating), U- and V-statistics.
The exercise sheets are on the moolde. Please apply there for this lecture.