Tssp-2024-25 — различия между версиями
Bdemeshev (обсуждение | вклад) |
Bdemeshev (обсуждение | вклад) |
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| Строка 31: | Строка 31: | ||
Lecture slides and class [https://github.com/bdemeshev/hse_panda_tssp_2024_2025/tree/main/course_notes notes] | Lecture slides and class [https://github.com/bdemeshev/hse_panda_tssp_2024_2025/tree/main/course_notes notes] | ||
| − | 2024-09- | + | 2024-09-16, lecture 3: Markov chain: communicating classes. Transient states. Recurrent states. |
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| + | 2024-09-24, lecture 4: Idea of generating function: describe collection of objects as a function and extract information from function. | ||
| + | How to extract E(X), E(X^2), E(XY), P(X=3) from a function that generates outcomes. Formal definition of probability generating function and moment generating function. | ||
Версия 23:31, 24 сентября 2024
Содержание
What-about
Course whitepaper
Course goals
侍には目標がなく道しかない [Samurai niwa mokuhyō ga naku michi shikanai]
A samurai has no goal, only a path.
Telegram chat
Grading
Stochastic Processes = 0.35 Halloween Exam + 0.40 Ded Moroz Exam + 0.25 Home Assignments
Time Series Analysis = 0.30 Mimoza Exam + 0.45 Sakura Exam + 0.25 Home Assignments
Home assignments
Home assignments have equal weights. You have 4 honey weeks for the whole year.
Exams
Samurai diary
Lecture slides and class notes
2024-09-16, lecture 3: Markov chain: communicating classes. Transient states. Recurrent states.
2024-09-24, lecture 4: Idea of generating function: describe collection of objects as a function and extract information from function. How to extract E(X), E(X^2), E(XY), P(X=3) from a function that generates outcomes. Formal definition of probability generating function and moment generating function.
Classes
Class video recordings
2024-09-06, class 1: First step analysis, 1.1 from StoPro.
More on first step analysis: section 2.7.2 in In2Pro
2024-09-13, class 2: First step analysis, 1.4 from StoPro.
2024-09-20, class 3: Classification of states in Markov chain, communicating classes, 3.1ab from StoPro.
Sources of Wisdom
StoPro: Problems in Stochastic Processes
In2Pro: Blitstein, Hwang, Introduction to probability.
MarkovTex: Representing Markov Chains in Latex.
Mchains Cambridge lectures on Markov chains.
Takis: Takis Konstantinopulos, One hundred solved exercises on Markov chains.
