Time Series and Stochastic Processes ada 21 22 — различия между версиями
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Bdemeshev (обсуждение | вклад) |
Bdemeshev (обсуждение | вклад) (→Semester II) |
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==== Week 1 ==== | ==== Week 1 ==== | ||
− | [https://github.com/bdemeshev/tssp_2021-22/raw/main/lectures/ | + | [https://github.com/bdemeshev/tssp_2021-22/raw/main/lectures/TSSP_m3_l1_done.pdf Lecture 1]. White noise, stationarity, ACF, PACF |
1.1. | 1.1. | ||
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==== Week 2 ==== | ==== Week 2 ==== | ||
− | [https://github.com/bdemeshev/tssp_2021-22/raw/main/lectures/ | + | [https://github.com/bdemeshev/tssp_2021-22/raw/main/lectures/TSSP_m3_l2_done.pdf Lecture 2]. |
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2.1. ETS model, forecasting, decomposition: [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-18-sem2_class_02_1_a.pdf pdf-a], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-18-sem2_class_02_1_b.pdf pdf-b], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-18-sem2_class_02_1_c.pdf pdf-c] | 2.1. ETS model, forecasting, decomposition: [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-18-sem2_class_02_1_a.pdf pdf-a], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-18-sem2_class_02_1_b.pdf pdf-b], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-18-sem2_class_02_1_c.pdf pdf-c] | ||
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==== Week 3 ==== | ==== Week 3 ==== | ||
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+ | [https://github.com/bdemeshev/tssp_2021-22/raw/main/lectures/TSSP_m3_l3_done.pdf Lecture 3]. | ||
3.1. Non stationarity of ETS(AAA), solutions of recurrence equation: [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-26-sem2_class_03_1_b.pdf, pdf-b] | 3.1. Non stationarity of ETS(AAA), solutions of recurrence equation: [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-01-26-sem2_class_03_1_b.pdf, pdf-b] | ||
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==== Week 4 ==== | ==== Week 4 ==== | ||
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+ | [https://github.com/bdemeshev/tssp_2021-22/raw/main/lectures/TSSP_m3_l4_done.pdf Lecture 4]. | ||
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4.1. Solutions of recurrence equation: [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-01-sem2_class_04_1_a_rus_arma_sols.pdf pdf-a], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-01-sem2_class_04_1_b_rus_arma_sols.pdf pdf-b], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-01-sem2_class_04_1_c_eng_arma_sols.pdf pdf-c]. | 4.1. Solutions of recurrence equation: [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-01-sem2_class_04_1_a_rus_arma_sols.pdf pdf-a], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-01-sem2_class_04_1_b_rus_arma_sols.pdf pdf-b], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-01-sem2_class_04_1_c_eng_arma_sols.pdf pdf-c]. | ||
4.2. Roots of lag and characteristic equation: [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-03-sem2_class_04_2_a_eng_roots.pdf pdf-a], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-03-sem2_class_04_2_b_rus_roots.pdf pdf-b], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-03-sem2_class_04_2_c_rus_roots.pdf pdf-c]. | 4.2. Roots of lag and characteristic equation: [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-03-sem2_class_04_2_a_eng_roots.pdf pdf-a], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-03-sem2_class_04_2_b_rus_roots.pdf pdf-b], [https://github.com/bdemeshev/tssp_2021-22/raw/main/notes/tssp_2021-22_2022-02-03-sem2_class_04_2_c_rus_roots.pdf pdf-c]. | ||
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+ | ==== Week 5 ==== | ||
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+ | [https://github.com/bdemeshev/tssp_2021-22/raw/main/lectures/TSSP_m3_l5_done.pdf Lecture 5] | ||
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+ | Estimation of ETS and ARMA: [https://colab.research.google.com/drive/1LE9T0KnnUBM-1OIzWT3INJzJjKd5-GdX?usp=sharing colab notebook] | ||
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+ | ==== Week 6 ==== | ||
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== Sources == | == Sources == |
Версия 12:44, 12 февраля 2022
General course info
- Boring official web page
- teams group: all class videos are there :)
Teachers and assistants
Lecturer: Peter Lukianchenko
Class teacher: Boris Demeshev
Semester I
Semester II
Do not forget about the home assignments!
Week 1
Lecture 1. White noise, stationarity, ACF, PACF
1.1.
1.2. Predictive interval for random walk, difference between mean, mode and median: pdf-b
Week 2
2.1. ETS model, forecasting, decomposition: pdf-a, pdf-b, pdf-c
2.2. AR(2), expected value, covariances: pdf-a, pdf-b, pdf-c
Week 3
3.1. Non stationarity of ETS(AAA), solutions of recurrence equation: pdf-b
3.2. Equations is not a process. Two problems from Econometrics Olympiad: pdf-a, pdf-b, pdf-c.
Week 4
4.1. Solutions of recurrence equation: pdf-a, pdf-b, pdf-c.
4.2. Roots of lag and characteristic equation: pdf-a, pdf-b, pdf-c.
Week 5
Estimation of ETS and ARMA: colab notebook
Week 6
Sources
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