Tssp-2023-24 — различия между версиями
Материал из Wiki - Факультет компьютерных наук
Bdemeshev (обсуждение | вклад) |
Bdemeshev (обсуждение | вклад) |
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==Log Book == | ==Log Book == | ||
− | ==== Semester I ==== | + | ==== Semester I: Stochastic Processes ==== |
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[http://www.statslab.cam.ac.uk/~rrw1/markov/ Cambridge course] on Markov chains | [http://www.statslab.cam.ac.uk/~rrw1/markov/ Cambridge course] on Markov chains | ||
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==Sources of Wisdom== | ==Sources of Wisdom== |
Версия 06:18, 6 сентября 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 1. 2023-09-04
Lecture. Markov chains, transition matrix, pdf
Class. Transition matrix, first step analysis, pdf by Maria
More:
Cambridge course on Markov chains
Sources of Wisdom
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