Exercise class: Tuesday 17:20 - 18:50 K3 (S. Nagy)
The knowledge of the statistics and probability theory at the level of
courses Mathematical Statistics 1 and 2
Probability Theory 1 (NMSA333)
and Linear regression (NMSA407).
Among others we will use the following concepts: almost sure convergence, convergence in probability, convergence in
distribution, law of large numbers and central limit theorem for independent and identically distributed random vectors.
A nice overview (in Czech language) of most of the results that are used in the course is available here.
(Assumed) content of the course:
Lecture material and actual information
Asymptotic methods - Delta Theorem, Moment estimators
Theory of maximum likelihood
Profile, conditional and marginal likelihood
M-estimators and Z-estimators, Robust estimation
Methods for missing data
Kernel density estimation
Kernel nonparametric regression