Tssp-2023-24: различия между версиями
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Bdemeshev (обсуждение | вклад) Нет описания правки |
Bdemeshev (обсуждение | вклад) |
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==== Semester I: Stochastic Processes ==== | ==== Semester I: Stochastic Processes ==== | ||
[https://www.youtube.com/playlist?list=PLnIS95ct9auXMX-4-ESGZvigU1w6kexw0 Practice playlist] | |||
'''Week 1. 2023-09-04''' | '''Week 1. 2023-09-04''' | ||
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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] | ||
More: | More: | ||
Версия от 11:33, 12 сентября 2023
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
Week 1. 2023-09-04
Lecture. Markov chains, transition matrix, pdf
Class. Transition matrix, first step analysis, pdf by Maria
Practice. MGF and first step analysis, pdf
More:
Cambridge course on Markov chains
Week 2. 2023-09-11
Lecture. Markov chains, classification of states, 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