Tssp-2022-23 — различия между версиями
(→Semester II) |
(→Semester II) |
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Строка 124: | Строка 124: | ||
Lecture. ARMA process, more ACF/PACF [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l2%263_DSBA3_2022.pdf pdf] | Lecture. ARMA process, more ACF/PACF [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l2%263_DSBA3_2022.pdf pdf] | ||
− | Class: recurrence equations and AR(1), Yule-Wolker equations for PACF [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w03a-ar1-more-pacf.pdf online- | + | Class: recurrence equations and AR(1), Yule-Wolker equations for PACF [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w03a-ar1-more-pacf.pdf online-A], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w03a-ar1-more-pacf.pdf online-B] |
'''Week 4. 2023-02-04 ''' | '''Week 4. 2023-02-04 ''' | ||
Строка 130: | Строка 130: | ||
Lecture. Forecasting with ARMA, ADF [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l4_DSBA3_2022.pdf pdf] | Lecture. Forecasting with ARMA, ADF [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l4_DSBA3_2022.pdf pdf] | ||
− | Class. Forecasting with AR, MA(infty) solutions | + | Class. Forecasting with AR, MA(infty) solutions [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w04a-ma-infinity-solution.pdf online-A], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w04b-ma-infinity-solution.pdf online-B] |
− | '''Week 5. | + | '''Week 5. 2023-02-11 ''' |
− | + | Lecture. Non-Stationary Time Series, Holt-Winter's exponential smoothing [https://github.com/bdemeshev/tssp_2022-23/raw/main/lectures/TSSP_m3_l5_done.pdf pdf] | |
+ | |||
+ | Class. ACF, PACF for ARMA(1,1), AR(2) [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w05a-arma11-pacf-interpretation online-A], [https://github.com/bdemeshev/tssp_2022-23/raw/main/online_classes/w05b-arma11-pacf-interpretation.pdf online-B] | ||
'''Week 6. plan ''' | '''Week 6. plan ''' | ||
ETS-model | ETS-model | ||
+ | |||
+ | Class. ETS(AAA) [https://github.com/bdemeshev/tssp_2022-23/blob/main/online_classes/w06a-ets-aaa.pdf, online-A] | ||
'''Week 7. plan ''' | '''Week 7. plan ''' |
Версия 17:25, 16 февраля 2023
Содержание
General course info
- Boring official web page
Grading
Fall grade = 0.3 HAs + 0.7 October Exam
Final grade = 0.2 Fall grade + 0.25 HAs + 0.15 December Midterm + 0.25 Spring Midterm + 0.15 Final Exam
Teachers and assistants
Lecturer: Peter Lukianchenko
Class teacher: Boris Demeshev, Sveta Popova, Maria Kirillova
Home assignments
Log Book
Semester I
Нажми "развернуть", чтобы просмотреть содержимое - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 🡣
Semester II
Week 1. 2023-01-14
Lecture. Intro to Time Series, stationarity, ACF, PACF pdf
Class: White noise, stationarity online-A, online-B
Week 2. 2023-01-21
Lecture. ARMA process, more ACF/PACF pdf
Class: ACF, PACF online-A, online-B
Week 3. 2023-01-28
Lecture. ARMA process, more ACF/PACF pdf
Class: recurrence equations and AR(1), Yule-Wolker equations for PACF online-A, online-B
Week 4. 2023-02-04
Lecture. Forecasting with ARMA, ADF pdf
Class. Forecasting with AR, MA(infty) solutions online-A, online-B
Week 5. 2023-02-11
Lecture. Non-Stationary Time Series, Holt-Winter's exponential smoothing pdf
Class. ACF, PACF for ARMA(1,1), AR(2) online-A, online-B
Week 6. plan
ETS-model
Class. ETS(AAA) online-A
Week 7. plan
Detrending, STL
Week 8. plan
GARCH
Week 9. plan
Volatility
Week 10. plan
Point, interval estimation
Week 11. plan
Total recall, midterm
Sources
- all past exams
- handwritten class notes
- Wiki 2020-21, Wiki 2021-22
- Git repo 2020-21, Git repo 2021-22
- TG chat 2022-23
- видео семинаров 2022-23 на русском
MC + MCMC
- James Norris, Markov chains (1998, no kernels)
- Cambridge course on Markov chains
- Chib and Greenberg, Understanding MH algorithm
- Casella, Explaining Gibbs Sampler
- Roberts and Rosenthal, General State Space Markov Chains
- Charles Geyer, MCMC lecture notes (with a little bit of kernels!)
Stochastic Calculus
- Zastawniak, Basic Stochastic Processes
Time Series
- Van der Vaart, Time Series
UCM
- Harvey Jaeger, Detrending, Stylized Facts and the Business Cycle
- João Tovar Jalles, Structural Time Series Models and the Kalman Filter