Date:
Event location: On Teams
Type: Cycle 36 - Mandatory Courses
All dates: via Teams
Mon 01/02 09.00 - 10.00
Tue 02/02 09.00 - 10.00
Wed 03/02 09.00 - 10.00
Thu 04/02 09.00 - 10.00
Fri 05/02 09.00 - 10.00
Mon 08/02 09.00 - 10.00
Tue 09/02 09.00 - 10.00
Wed 10/02 09.00 - 10.00
Thu 11/02 09.00 - 10.00
Fri 12/02 09.00 - 10.00
* Topics:
- Some Prerequisites: Convergence of random variables, Slutsky theorem, Notations Op(_) and op(_), Useful probabilistic inequalities
- Delta method. Variance-stabilizing transformations. Skewness reducing transformations
- Ordered statistics. Asymptotic distribution of extreme values
- Quantiles and limit distributions. Sample moments
- M-estimators (and Z-estimators), consistency and asymptotic normality
- First-order asymptotics of likelihood inference
- (If time allows) U-statistics, asymptotic properties
* References:
Barndorff-Nielsen, O.E., Cox, D.R. (1989). Asymptotic Techniques for Use in Statistics. Chapman and Hall, London.
Casella, G. and Berger, R.L. (1990). Statistical Inference, Wadsworth& Brooks/Cole.
Christopher G. Small (2010). Expansions and Asymptotics for Statistics, Chapman & Hall/CRC (chapters 4 and 5)
van der Vaart A.W. (2000). Asymptotic Statistics. CUP