Agendas

Minor updates might occur during the semester, and slides and scripts will be uploaded before each lecture.

Day no.	Date	Lecturer	Subject	Material	Exercises
1	2/9	Tobias K. S. Ritschel	Kernel estimators and their applications in time series analysis Non-parametric and conditional-parametric models Mixture approximations Lag-dependence functions	Intro Slides Videos	lecture01_kernel_methods_approximate_pdf.txt lecture01_kernel_methods_conditional_mean.txt scripts
2	9/9	Erik Lindström	Non-linear time series models Generalized transfer functions Volterra series	Slides Slides (cons.) Slides (crypto.)
3	16/9	Tobias K. S. Ritschel	State Space Models and State Space Modeling Ordinary Kalman Filter and extended filters Non-linear state space models Generalized State Space models	Slides (recap) Slides Videos	Classroom exercises
4	23/9	Teaching Assistant	Computer exercises 1
5	30/9	Erik Lindström	Parameter estimation in non-linear models Case studies	Non-linear TS slides Non-linear TS scripts
6	7/10	Jan Klopppenborg Møller	Forecast reconciliation Multivariate forecast evaluation	slides_Forecast_Recon slides_Multi_Fore_Eval Bjerregaard_et_al_2021 Bergsteinson_et_al_2021 HeirarchicalGLM_moller_et_al	Exercise06 Exercise06_data Forecast_eval_sim_ex
7	21/10	Erik Lindström	Stochastic differential equations Ito Calculus Exact and approximate filters	SDE slides SDE scripts
8	28/10	Teaching Assistant	Computer exercises 2
9	4/11	Jan Klopppenborg Møller	Estimation of linear and (some) non-linear SDEs Modelling using stochastic differential equations
10	11/11	Teaching Assistant	Computer exercises 3
11	18/11	Erik Lindström	Recursive estimation Non stationary systems	Recursive slides Recursive slides Iter. Filt. Efficient Iterated Filtering Recursive scripts
12	25/11	Jan Klopppenborg Møller Tobias K. S. Ritschel	Modelling non-stationary systems Experimental design for dynamic system modelling Prediction in non-linear models
13	2/12	Teaching Assistant	Computer exercises 4
	17-18/12	Exam