Stochastic analysis 2021 2022 — различия между версиями

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== Recommended literature (1st term) ==
 
== Recommended literature (1st term) ==
*http://www.statslab.cam.ac.uk/~james/Markov/ - Cambridge lecture notes on discrete-time Markov Chains
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*http://www.statslab.cam.ac.uk/~james/Markov/ - Cambridge lecture notes on discrete-time Markov Chains;
*https://link.springer.com/book/10.1007%2F978-3-319-97704-1 - book by E. Moulines et al, you are mostly interested in chapters 1,2,7 and 9 (book is accessible for download through HSE network)
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*https://link.springer.com/book/10.1007%2F978-3-319-97704-1 - book by E. Moulines et al, you are mostly interested in chapters 1,2,7 and 9 (book is accessible for download through HSE network);
*https://link.springer.com/book/10.1007%2F978-3-319-62226-2 - Stochastic Calculus by P. Baldi, good overview of conditional probabilities and expectations (part 4, also accessible through HSE network)
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*https://link.springer.com/book/10.1007%2F978-3-319-62226-2 - Stochastic Calculus by P. Baldi, good overview of conditional probabilities and expectations (part 4, also accessible through HSE network);
*https://link.springer.com/book/10.1007%2F978-1-4419-9634-3 - Probability for Statistics and Machine Learning by A. Dasgupta, chapter 19 (MCMC), also accessible through HSE network
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*https://link.springer.com/book/10.1007%2F978-1-4419-9634-3 - Probability for Statistics and Machine Learning by A. Dasgupta, chapter 19 (MCMC), also accessible through HSE network;
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*http://th.if.uj.edu.pl/~gudowska/dydaktyka/Oksendal.pdf - Stochastic Differential Equations by Bernt Oksendal, chapters 3-4-5 provide a construction of the Stochastic integral and all required information on SDE's.

Версия 01:56, 10 ноября 2021

Lecturers and Seminarists

Lecturer Naumov Alexey [anaumov@hse.ru] T924
Seminarist Samsonov Sergey [svsamsonov@hse.ru] T926

About the course

This page contains materials for Stochastic Analysis course in 2021/2022 year, mandatory one for 1st year Master students of the Statistical Learning Theory program (HSE and Skoltech).

Grading

The final grade consists of 3 components (each is non-negative real number from 0 to 10, without any intermediate rounding) :

  • OHW for the hometasks
  • OMid-term for the midterm exam
  • OExam for the final exam

The formula for the final grade is

  • OFinal = 0.3*OHW + 0.3*OMid-term + 0.4*OExam + 0.1*OBonus HW

with the usual (arithmetical) rounding rule.

Table with grades

Lectures

Seminars

Homeworks

Exam

Midterm

Midterm will take place on Saturday, 13.11.2020, at 11:00. Midterm is open-book, all materials are allowed. Midterm will take 3 hours and it will contain 6 problems. Solving any 5 of them will give you the maximal grade.

List of topics

Recommended literature (1st term)