TMA4265 Stochastic Processes, Autumn 2014
Lecture plan
This schedule is tentative, changes will appear.
R = Ross, Introduction to probability models, 11th edition, Academic Press
| Week | Date | Topics | Reading | Additional Material |
|---|---|---|---|---|
| 34 | 18.08 | Review: Probability and random variables | R: Ch. 1 | Slides (minor changes 25.08.2014 Introduction to R |
| R introduction | ||||
| 20.08 | Review: Probability and random variables | R: Ch. 1 and 2 | continued with slides | |
| 35 | 25.08 | Finish chap. 1-2, start conditional probability and expectation | R: Ch. 2, Ch.3 .1, 3.2, 3.3 | |
| 27.08 | NO LECTURE: Self study - conditional probability and expectation | R: Ch. 3.4 | Lecture notes | |
| 36 | 01.09 | conditional probability and expectation | R: Ch. 3.5, 3.6.3 | |
| 03.09 | Discrete-time Markov chains | R: Ch. 4.1, 4.2 | InterRail example | |
| 37 | 08.09 | Discrete-time Markov chains | R: Ch. 4.3 | MC accessibility, R-code for Markov chain simulation (updated 15.09) |
| 10.09 | Discrete-time Markov chains | R: Ch. 4.3 | Recurrent and transient | |
| 38 | 15.09 | Discrete-time Markov chains | R: Ch. 4.4 | Periodicity, positive/null recurrence R-code for n-step transition matrix |
| 17.09 | Discrete-time Markov chains | R: Ch. 4.4, 4.6 | ||
| 39 | 22.09 | Discrete-time Markov chains | R: Ch. 4.6, 4.8 | R-code for time spent in transient states |
| 24.09 | Discrete-time Markov chains | R: Ch. 4.8, Definition of learning objectives, Summary, Exam problems | Slides, R-code to first exam question, R-code to second (chess) exam question | |
| 40 | 29.09 | Discrete-time Markov chains | R: Ch. 4.9 | R-code for Poisson simulation |
| 01.10 | Poisson-process | R: Ch. 4.9 (finish), 5.1, 5.2 | MCMC slides, Poisson simulation using MCMC | |
| 41 | 06.10 | Work on PROJECT (Nullrommet 380A) | ||
| 08.10 | Work on PROJECT (Nullrommet 380A) | |||
| 42 | 13.10 | Poisson-process | R: Ch. 5.3 | Slides for Poisson process |
| 15.10 | Poisson-process | R: Ch. 5.3 | ||
| 43 | 20.10 | Continuous-time Markov chains | R: Ch. 6.1, 6.2, 6.3 | Slides for continuous-time MC R-code for Yule-process, |
| 22.10 | Continuous-time Markov chains | R: Ch. 6.3, 6.4 | ||
| 44 | 27.10 | Continuous-time Markov chains | R: Ch. 6.4, 6.5 | Slides for continuous-time MC II |
| 29.10 | Continuous-time Markov chains | R: Ch. 6.5, 6.6 | ||
| 45 | 03.11 | Continuous-time Markov chains + Queueing theory | R: Ch. 6.6, 8.1, 8.2 | Slides for time-reversibility + introduction to queueing theory |
| 05.11 | Self study: no lecture | R: Ch. 8.3 + weekly exercises | ||
| 46 | 10.11 | Queueing theory | R: Ch. 8.3.1, 8.3.2, 8.3.4 | Slides for queuing theory II |
| 12.11 | Queueing theory | R: Ch.8.5, 8.9.1, 8.9.2 | Slides for chapter 8.5 | |
| 47 | 17.11 | Brownian motion | R: Ch. 8.9.2 + 10.1 - 10.3 | Slides for Brownian motion |
| 19.11 | Summary | Slides |