Tssp-2023-24 — различия между версиями
Bdemeshev (обсуждение | вклад) |
Bdemeshev (обсуждение | вклад) (→Semester I: Stochastic Processes) |
||
(не показано 15 промежуточных версии 2 участников) | |||
Строка 2: | Строка 2: | ||
− | + | Lecturer: [https://www.hse.ru/org/persons/14276760 Peter Lukianchenko] | |
+ | Practice and problem solving: [https://www.hse.ru/staff/bbd/ Boris Demeshev], Friday 16:20-17:40 Moscow time, [https://zoom.us/j/8126338383 zoom] | ||
− | + | Class teacher: [https://www.hse.ru/org/persons/14288706 Sveta Popova], [https://www.hse.ru/org/persons/785361814 Maria Kirillova] | |
− | + | ==Log Book == | |
− | + | ==== Semester I: Stochastic Processes ==== | |
− | + | [https://www.youtube.com/playlist?list=PLnIS95ct9auXMX-4-ESGZvigU1w6kexw0 Practice playlist] | |
+ | [https://raw.githubusercontent.com/bdemeshev/tssp_2023-24/main/ha/tssp_ha.pdf home assignments] | ||
+ | '''Week 0. 2023-09-02''' | ||
+ | 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] | |
+ | 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: | |
− | + | [http://www.statslab.cam.ac.uk/~rrw1/markov/ Cambridge course] on Markov chains | |
− | + | '''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''' | ||
+ | |||
+ | Lecture + practice. Poisson process, [https://github.com/bdemeshev/tssp_2023-24/raw/main/practice/practice-03.pdf pdf], [https://bdemeshev.github.io/tssp_2023-24/poisson-process.html notes in progress] | ||
+ | |||
+ | Class. Stationary distribution, convergence, [https://github.com/bdemeshev/tssp_2023-24/raw/main/classes/HSE_sem3.pdf pdf by Maria] | ||
More: | More: | ||
− | [http://www.statslab.cam.ac.uk/~rrw1/markov/ Cambridge course] on Markov chains | + | [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] | ||
+ | |||
+ | '''Week 5. 2023-09-16''' | ||
+ | |||
+ | Practice. Conditional expected value and variance, [https://github.com/bdemeshev/tssp_2023-24/raw/main/practice/practice-05.pdf pdf] | ||
+ | |||
+ | Lecture. Sigma-algebras, [https://github.com/bdemeshev/tssp_2023-24/blob/main/lectures/TSSP_23_m1_l6_v2.pdf pdf] | ||
+ | |||
+ | '''Week 6. 2023-09-16''' | ||
+ | |||
+ | Practice. Sigma-algebras, [https://github.com/bdemeshev/tssp_2023-24/raw/main/practice/practice-06.pdf pdf] | ||
+ | |||
+ | Lecture. | ||
+ | |||
+ | ==Sources of Wisdom== | ||
+ | |||
+ | * [https://github.com/bdemeshev/tssp_exams/raw/main/tssp_exams.pdf all past exams] | ||
+ | * [https://github.com/bdemeshev/stochastic_pro/raw/main/stochastic_pro.pdf a lot of problems...] (under construction) | ||
+ | * [https://t.me/spts2023 TG chat 2023-24] | ||
+ | * [https://github.com/mavam/stat-cookbook/releases/download/0.2.7/stat-cookbook.pdf Statistics cookbook] | ||
+ | * [http://wiki.cs.hse.ru/Time_Series_and_Stochastic_Processes_ada_20_21 Wiki 2020-21], [http://wiki.cs.hse.ru/Time_Series_and_Stochastic_Processes_ada_21_22 Wiki 2021-22], [http://wiki.cs.hse.ru/Tssp-2022-23 Wiki 2022-23] | ||
+ | |||
+ | |||
+ | === MC + MCMC === | ||
+ | |||
+ | * [http://www.statslab.cam.ac.uk/~rrw1/markov/ Cambridge course] on Markov chains | ||
+ | |||
+ | * Chib and Greenberg, [https://eml.berkeley.edu/reprints/misc/understanding.pdf Understanding MH algorithm] | ||
+ | |||
+ | * Casella, [http://biostat.jhsph.edu/~mmccall/articles/casella_1992.pdf Explaining Gibbs Sampler] | ||
+ | |||
+ | * Roberts and Rosenthal, [https://projecteuclid.org/euclid.ps/1099928648 General State Space Markov Chains] | ||
+ | |||
+ | * [https://chi-feng.github.io/mcmc-demo Visualization of MCMC methods] | ||
+ | |||
+ | * Charles Geyer, [http://www.stat.umn.edu/geyer/f05/8931/n1998.pdf MCMC lecture notes] (with a little bit of kernels!) | ||
+ | |||
+ | === Stochastic Calculus === | ||
+ | |||
+ | * Zastawniak, Basic Stochastic Processes | ||
+ | |||
+ | * [https://github.com/bdemeshev/sc401/raw/master/matek2_collect/matek2_collection.pdf Exams of ICEF master course] | ||
+ | |||
+ | * [https://bdemeshev.github.io/sc401/ Заметки магистерского курса МИЭФ (рус)] | ||
+ | |||
+ | * [https://github.com/bdemeshev/sc_book/raw/master/sc_book.pdf Черновик учебника (рус)] | ||
+ | |||
+ | * [https://github.com/bdemeshev/sc401/raw/master/sc_pset/sc_problems_main.pdf Черновик задачника (рус)] | ||
+ | |||
+ | === Time Series === | ||
+ | |||
+ | * [https://otexts.com/fpp3/ Forecasting principles and practice (R)] | ||
+ | |||
+ | * [https://www.stat.pitt.edu/stoffer/tsa4/ Shumway, Stoffer Time Series Analysis] | ||
+ | |||
+ | * [https://faculty.chicagobooth.edu/ruey-s-tsay/teaching Ruey Tsay web page] | ||
+ | |||
+ | * Van der Vaart, [http://www.math.leidenuniv.nl/~avdvaart/timeseries/index.html Time Series] | ||
+ | |||
+ | * [https://github.com/bdemeshev/ts_pset Черновик задачника (рус)] | ||
+ | |||
+ | ==== UCM ==== | ||
+ | |||
+ | * Harvey Jaeger, [https://www.statsmodels.org/dev/examples/notebooks/generated/statespace_structural_harvey_jaeger.html Detrending, Stylized Facts and the Business Cycle] | ||
+ | |||
+ | * João Tovar Jalles, [https://core.ac.uk/download/pdf/6242335.pdf Structural Time Series Models and the Kalman Filter] | ||
+ | |||
+ | * [https://pdfs.semanticscholar.org/0bc8/582016086017763b93e87ad8640ec1816aeb.pdf Harvey, Forecasting with UCM] | ||
+ | |||
+ | * [http://www.chadfulton.com/fulton_statsmodels_2017/ Chad Fulton] | ||
+ | |||
+ | * [https://robjhyndman.com/uwafiles/9-StateSpaceModels.pdf Rob Hyndman, State Space Models] |
Текущая версия на 18:41, 13 октября 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
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, notes in progress
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
Week 5. 2023-09-16
Practice. Conditional expected value and variance, pdf
Lecture. Sigma-algebras, pdf
Week 6. 2023-09-16
Practice. Sigma-algebras, pdf
Lecture.
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