Syllabus
1. Robust regression.
2. Logistic regression.
3. Multinomial regression.
4. Poisson regression.
5. Truncated and inflated data.
6. Survival analysis.
7. Analysis of panel/longitudinal data.
Annotation
Machine learning + statistical inference = statistical learning. Methods of statistical learning for categorical
(unordered and ordered), nominal (discrete and continuous), truncated, censored, extremal, and clustered data.
Modeling (not only) financial, economic, and insurance processes. Practical exercises and problems from econometrics, model testing, parameter estimation, prediction in stochastic models and their diagnostics.
Computational demanding stochastic techniques.