Time Series and Stochastic Processes ada 21 22 — различия между версиями
Материал из Wiki - Факультет компьютерных наук
Bdemeshev (обсуждение | вклад) (→MC + MCMC) |
Bdemeshev (обсуждение | вклад) (→Sources) |
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* [http://wiki.cs.hse.ru/Time_Series_and_Stochastic_Processes_ada_20_21 Wiki 2020-2021] | * [http://wiki.cs.hse.ru/Time_Series_and_Stochastic_Processes_ada_20_21 Wiki 2020-2021] | ||
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* [https://github.com/bdemeshev/tssp/tree/master/2020_2021 Git repo 2020-2021] | * [https://github.com/bdemeshev/tssp/tree/master/2020_2021 Git repo 2020-2021] | ||
+ | * [https://github.com/bdemeshev/tssp_2021-22/ Git repo 2021-2022] | ||
* [https://github.com/mavam/stat-cookbook/releases/download/0.2.6/stat-cookbook.pdf Statistics cookbook] | * [https://github.com/mavam/stat-cookbook/releases/download/0.2.6/stat-cookbook.pdf Statistics cookbook] |
Версия 20:03, 27 октября 2021
Содержание
General course info
- Boring official web page
- teams group: all class videos are there :)
Teachers and assistants
Lecturer: Peter Lukianchenko
Class teacher: Boris Demeshev
Week progress
Week 01
Lecture:
Class: First step analysis, expected time to get HTH.
Week 02
Lecture:
Class: Markov chain states classification
Week 03
Lecture:
Class: Poisson process.
Week 04
Lecture:
Class: Conditional expected value. Conditional variance.
Week 05
Lecture:
Class: Sigma-algebras, measurability. Conditional expected value with respect to sigma-algebra.
Week 06
Lecture:
Class: Probability limit, Moment generating function
Midterm
The long-awaited midterm will be on 28 October, 10:00 - 12:00.
Duration: 120 minutes. No proctoring.
Topics:
- First step analysis
- Classification of states and classes of MC.
- Conditional expected value (two views).
- Poisson process.
- Sigma algebras.
- Probability limit
- Moment generating function
Sources
MC + MCMC
- James Norris, Markov chains (1998, no kernels)
- 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