TMA4265 Stochastic Processes, Autumn 2015
Learning objectives:
Schedule:
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. 1,2 | Chapter 1 and 2 , Notes document camera (only) |
| R introduction | introR.txt | |||
| 21.08 | Review: Random variables; start conditional probability and expectation | R: Ch. 2, Ch. 3.1, 3.2 | continue with slides to finish chapter 2, Notes document camera (only) | |
| 35 | 25.08 | Conditional probability and expectation | R: Ch. 3.2 - 3.4 | Notes document camera (only) (minor correction page 2 second line from the bottom: change equal to approx sign) |
| 28.08 | Conditional probability and expectation | R: Ch. 3.4, 3.5, 3.6.3 | Slides used for Chapter 3 , Notes document camera (only) | |
| 36 | 01.09 | Start Markov chains | R: Ch. 3.6.3, 4.1, 4.2 | Slides used, Notes document camera (only) |
| 04.09 | Markov chains | R: Ch. 4.2, 4.3 | Notes document camera (only) , Take home summary | |
| 37 | 08.09 | Markov chains | R: Ch. 4.3, 4.4 | Notes document camera (only) , slides |
| 11.09 | Markov chains | R: Ch. 4.4 | Slides used, Notes for null-recurrent example and proof of theorem for limiting distribution, Take home summary , | |
| 38 | 14.09 | Markov chains | R: Ch. 4.4, 4.6 | Notes document camera (only) Caution: Small comment added on bottom of page 5, R-Code to simulate Markov chain |
| 18.09 | SELF STUDY (No lecture) | R: Ch. 4.5.1, 4.7 | TODO list , Additional material for Section 4.5.1, Solution to problems on todo list | |
| 39 | 22.09 | Markov chains | R: Ch. 4.6, 4.8 | Take home summary |
| 25.09 | Markov chains | R: Ch. 4.8 | Notes document camera (only) | |
| 40 | 29.09 | Markov chains: MCMC | R: Ch. 4.9 | Notes document camera (only) , Slides (updated 01.10, 20:35, fixed mistakes in toy examples), R-code for MCMC sampling from Poisson distribution |
| 02.10 | Poisson processes | R: Ch. 5.1, 5.2, 5.3 | Notes document camera (only) (compared to lecture minor addition on page 3 (pink) regarding constant failure rate) | |
| 41 | 06.10 | Poisson processes | R: Ch. 5.3 | Notes document camera (only) , Slides , R-code for simulating fishing example to check expected total number of fish and expected total fishing time (updated 6.10, 16:55) |
| 09.10 | Poisson processes | R: Ch. 5.3 | Notes document camera (only) | |
| 42 | 13.10 | Continuous-time Markov chains | R: Ch. 6.1, 6.2, 6.3 | Slides , Notes document camera (only) , R-function to simulate Yule process (birth process with linear birth rate) |
| 16.10 | Continuous-time Markov chains | R: Ch. 6.3, 6.4 | Slides , Notes document camera (only) | |
| 43 | 20.10 | Continuous-time Markov chains | R: Ch. 6.4, 6.5 | Slides , Notes document camera (only) |
| 23.10 | Continuous-time Markov chains | R: Ch. 6.5, 6.6 | Slides , Notes document camera (only) | |
| 44 | 27.10 | Queueing theory | R: Ch. 8.1 - 8.2, 8.3.1 | Slides , Notes document camera (only) |
| 30.10 | Queueing theory | 8.3.2, 8.3.3, 8.3.4 | Slides , Notes document camera (only) | |
| 45 | 03.11 | Project (Nullrommet 380A) | ||
| 06.11 | Project (Nullrommet 380A) | |||
| 46 | 10.11 | Queueing theory | R: Ch. 8.5, 8.9.1, 8.9.2 | Slides , Notes document camera (only) , Notes for section 8.9.2 as outlined in course. If there are things to clarify in the derivations for 8.9.2, please let me know coming Friday |
| 13.11 | Brownian motion | R: Ch. 10.1-10.3 | Slides , Notes document camera (only) | |
| 47 | 17.11 | Brownian motion | R: Ch. 10.2-10.3 | Slides , Notes document camera (only) |
| 20.11 | Summary | Slides |