Tssp-2022-23 — различия между версиями

Версия 20:53, 22 марта 2023

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

Actual grades: xlsx, html

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. 2023-02-18

Lecture. ETS-model pdf

Class. ETS(AAA) online-A, online-B

Week 7. 2023-02-25

Lecture. GARCH pdf

Week 8. 2023-03-04

Lecture. UOL - point, interval estimators pdf

Week 9. 2023-03-11

Lecture. UOL - Fisher info pdf

Class. Fisher info

Week 10. 2023-03-18

Lecture. UOL

Week 11. 2023-03-25

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

• Statistics cookbook

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

• Visualization of MCMC methods

• Charles Geyer, MCMC lecture notes (with a little bit of kernels!)

Stochastic Calculus

• Zastawniak, Basic Stochastic Processes

• Exams of ICEF master course

• Заметки магистерского курса МИЭФ (рус)

• Черновик учебника (рус)

• Черновик задачника (рус)

Time Series

• Forecasting principles and practice (R)

• Shumway, Stoffer Time Series Analysis

• Ruey Tsay web page

• Van der Vaart, Time Series

• Черновик задачника (рус)

UCM

• Harvey Jaeger, Detrending, Stylized Facts and the Business Cycle

• João Tovar Jalles, Structural Time Series Models and the Kalman Filter

• Harvey, Forecasting with UCM

• Chad Fulton

• Rob Hyndman, State Space Models