Tssp-2024-25 — различия между версиями
Bdemeshev (обсуждение | вклад) |
Bdemeshev (обсуждение | вклад) |
||
| Строка 38: | Строка 38: | ||
Class [https://e.pcloud.link/publink/show?code=kZDCKPZ6dPB3lXGHrhUzqeC7wkVfyaLsAq7 video recordings] | Class [https://e.pcloud.link/publink/show?code=kZDCKPZ6dPB3lXGHrhUzqeC7wkVfyaLsAq7 video recordings] | ||
| − | 2024-09-06: First step analysis, | + | 2024-09-06, class 1: First step analysis, 1.1 from [https://github.com/bdemeshev/stochastic_pro/raw/main/stochastic_pro.pdf StoPro]. |
More on first step analysis: section 2.7.2 in [https://projects.iq.harvard.edu/stat110/home In2Pro] | More on first step analysis: section 2.7.2 in [https://projects.iq.harvard.edu/stat110/home In2Pro] | ||
| − | 2024-09-13: First step analysis, | + | 2024-09-13, class 2: First step analysis, 1.4 from [https://github.com/bdemeshev/stochastic_pro/raw/main/stochastic_pro.pdf StoPro]. |
| + | |||
| + | 2024-09-20, class 3: Classification of states in Markov chain, communicating classes, 3.1ab from [https://github.com/bdemeshev/stochastic_pro/raw/main/stochastic_pro.pdf StoPro]. | ||
== Sources of Wisdom == | == Sources of Wisdom == | ||
Версия 20:52, 22 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-
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.
