Time Series and Stochastic Processes ada 21 22 — различия между версиями

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(MC + MCMC)
(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]
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* [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

General course info


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)

Stochastic Calculus

  • Zastawniak, Basic Stochastic Processes

Time Series

UCM

Grading System