Tssp-2023-24 — различия между версиями
Материал из Wiki - Факультет компьютерных наук
Bdemeshev (обсуждение | вклад) |
Bdemeshev (обсуждение | вклад) (→Log Book) |
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| Строка 16: | Строка 16: | ||
[https://www.youtube.com/playlist?list=PLnIS95ct9auXMX-4-ESGZvigU1w6kexw0 Practice playlist] | [https://www.youtube.com/playlist?list=PLnIS95ct9auXMX-4-ESGZvigU1w6kexw0 Practice playlist] | ||
| − | + | '''Week 0. 2023-09-02''' | |
| − | '''Week | + | |
Lecture. Markov chains, transition matrix, [https://github.com/bdemeshev/tssp_2023-24/raw/main/lectures/TSSP_23_m1_l1%202.pdf pdf] | Lecture. Markov chains, transition matrix, [https://github.com/bdemeshev/tssp_2023-24/raw/main/lectures/TSSP_23_m1_l1%202.pdf pdf] | ||
| + | |||
| + | '''Week 1. 2023-09-04''' | ||
Class. Transition matrix, first step analysis, [https://github.com/bdemeshev/tssp_2023-24/raw/main/classes/HSE_sem1.pdf pdf by Maria] | Class. Transition matrix, first step analysis, [https://github.com/bdemeshev/tssp_2023-24/raw/main/classes/HSE_sem1.pdf pdf by Maria] | ||
Practice. MGF and first step analysis, [https://github.com/bdemeshev/tssp_2023-24/raw/main/practice/practice-01.pdf pdf] | Practice. MGF and first step analysis, [https://github.com/bdemeshev/tssp_2023-24/raw/main/practice/practice-01.pdf pdf] | ||
| + | |||
| + | Lecture. Markov chains, classification of states, [https://github.com/bdemeshev/tssp_2023-24/raw/main/lectures/TSSP_23_m1_l2.pdf pdf] | ||
More: | More: | ||
| Строка 31: | Строка 34: | ||
'''Week 2. 2023-09-11''' | '''Week 2. 2023-09-11''' | ||
| − | + | Practice. More generating functions and first step analysis, [https://github.com/bdemeshev/tssp_2023-24/raw/main/practice/practice-02.pdf pdf] | |
| + | |||
| + | Lecture. Convergence. [https://github.com/bdemeshev/tssp_2023-24/raw/main/lectures/TSSP_23_m1_l3.pdf pdf] | ||
'''Week 3. 2023-09-16''' | '''Week 3. 2023-09-16''' | ||
| − | Lecture. | + | Lecture + practice. Poisson process, [https://github.com/bdemeshev/tssp_2023-24/raw/main/practice/practice-03.pdf pdf] |
| − | + | Class. Stationary distribution, convergence, [https://github.com/bdemeshev/tssp_2023-24/raw/main/classes/HSE_sem3.pdf pdf by Maria] | |
| + | |||
| + | More: | ||
| + | |||
| + | [https://towardsdatascience.com/the-inspection-paradox-is-everywhere-2ef1c2e9d709 Inspection paradox], [https://www.math.ucla.edu/~mason/papers/frym-WTP-published.pdf Waiting time paradox], [https://en.wikipedia.org/wiki/Friendship_paradox Friendship paradox] | ||
| + | |||
| + | '''Week 4. 2023-09-16''' | ||
| + | |||
| + | Practice. Convergence, [https://github.com/bdemeshev/tssp_2023-24/raw/main/practice/practice-04.pdf pdf] | ||
| + | |||
| + | Lecture. Conditional expected value, [https://github.com/bdemeshev/tssp_2023-24/raw/main/lectures/TSSP_23_m1_l4.pdf pdf] | ||
==Sources of Wisdom== | ==Sources of Wisdom== | ||
Версия 19:23, 30 сентября 2023
Содержание
General course info
Lecturer: Peter Lukianchenko
Practice and problem solving: Boris Demeshev, Friday 16:20-17:40 Moscow time, zoom
Class teacher: Sveta Popova, Maria Kirillova
Log Book
Semester I: Stochastic Processes
Practice playlist Week 0. 2023-09-02
Lecture. Markov chains, transition matrix, pdf
Week 1. 2023-09-04
Class. Transition matrix, first step analysis, pdf by Maria
Practice. MGF and first step analysis, pdf
Lecture. Markov chains, classification of states, pdf
More:
Cambridge course on Markov chains
Week 2. 2023-09-11
Practice. More generating functions and first step analysis, pdf
Lecture. Convergence. pdf
Week 3. 2023-09-16
Lecture + practice. Poisson process, pdf
Class. Stationary distribution, convergence, pdf by Maria
More:
Inspection paradox, Waiting time paradox, Friendship paradox
Week 4. 2023-09-16
Practice. Convergence, pdf
Lecture. Conditional expected value, pdf
Sources of Wisdom
- all past exams
- a lot of problems... (under construction)
- TG chat 2023-24
- Statistics cookbook
- Wiki 2020-21, Wiki 2021-22, Wiki 2022-23
MC + MCMC
- 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
