Syllabus
Clippings from the asymptotic theory - Delta Theorem and Moment Estimators
Theory of maximum likelihood
Profile, conditional and marginal likelihood
M-estimators and Z-estimators
Robust estimation
Quantile regression
EM-algorithm
Methods for missing data
Bootstrap
Kernel density estimation
Kernel nonparametric regression
Annotation
Modern methods of statistical inference based on maximum likelihood theory and its generalizations.
Fundamentals of nonparametric and robust methods. Methods for missing observations.