MATH4240 - Stochastic Processes - 2016/17
Announcement
- Welcome to the course! No tutorial lecture in the 1st week. Here is the tentative schedule of the course: [Download file]
- Quiz 1: in class on Feb 17; cover all lectures up to Feb 10.
- Midterm Test: 1) Time and place: 9:30am-10:15am on March 13, MMW 702 (Tutorial lecture will be canceled for the test). 2) Covers: up to all (class and tutorial) lectures on March 6.
- Quiz 2: in class on April 7; covers: 1) Periodicity and long-time behaviour of Markov chains, and 2) Basic properties of MJP, particularly Poisson process.
- Tutorial on April 10 will change to course lecture, and course lecture on April 21 will change to Tutorial.
General Information
Lecturer
-
Prof. Renjun DUAN
- Office: LSB 206
- Tel: 39437977
- Email:
- Office Hours: 9:00AM-10:15AM on each Friday or by appointment
Teaching Assistant
-
Mr. Shilei KONG
- Office: LSB 222A
- Tel: 39433575
- Email:
- Office Hours: Mo 1:30PM - 4:30PM, Tu 2:30PM - 4:30PM, Th 1:30PM - 4:30PM
Time and Venue
- Lecture: Mo 10:30AM - 12:15PM, Mong Man Wai Bldg 702; Fr 10:30AM - 11:15AM, Lady Shaw Bldg LT3
- Tutorial: Mo 9:30AM - 10:15AM, Mong Man Wai Bldg 702
Course Description
Bernoulli processes and sum of independent random variables, Poisson processes, times of arrivals, Markov chains, transient and recurrent states, stationary distribution of Markov chains, Markov pure jump processes, and birth and death processes. Students taking this course are expected to have knowledge in probability.
Textbooks
- Introduction to Stochastic Processes by Hoel, Port and Stone (Chapter 1, Chapter 2, and Chapter 3 ONLY)
References
- Essentials of Stochastic Processes by Durrett (many applied examples)
- Introduction to Stochastic Processes by Lawler (condense)
- Basic Stochastic Processes by Brzezniak and Zastawniak (more theoretical)
- Denumerable Markov chains by Wolfgang Woess (more topics on Markov chains)
- Stochastic Processes by Sheldon Ross (more advanced)
Lecture Notes
- A Historical Note
- Summary of Chapter 0
- Summary of Chapter 1 (updated on Feb 13)
- Summary of Chapter 2 (updated on Mar 13)
- Summary of Chapter 3 (updated on April 10)
- Corrections (updated on April 10)
Tutorial Notes
- Tutorial Note 1 (2017.1.16)
- Tutorial Note 2 (2017.1.23)
- Tutorial Note 3 (2017.2.6)
- Tutorial Note 4 (2017.2.13)
- Tutorial Note 5 (2017.2.20)
- Tutorial Note 6 (2017.2.27)
- Tutorial Note 7 (2017.3.6)
- Tutorial Note 8 (2017.3.20)
- Tutorial Note 9-10 (2017.3.27 / 4.3)
- Tutorial Note 11 (2017.4.21)
Assignments
Quizzes and Exams
Solutions
- Suggested Solution to Homework 1
- Suggested Solution to Homework 2
- Suggested Solution to Homework 3
- Suggested Solution to Homework 4
- Suggested Solution to Homework 5
- Suggested Solution to Homework 6
Assessment Scheme
| Homework (about four times) | 10% | |
| Two Quizzes (Quiz 1 is on Feb 17; Quiz 2 is on Apr 7) | 15% | |
| Midterm (March 13) | 25% | |
| Final Exam (The date TBA by the University) | 50% |
Useful Links
- Probability, Mathematical Statistics, Stochastic Processes (An open source)
- Essentials of Stochastic Processes (Richard Durrett)
- Markov Chains (James Norris)
- A First Course in Probability (Sheldon Ross)
Honesty in Academic Work
The Chinese University of Hong Kong places very high importance on honesty in academic work submitted by students, and adopts a policy of zero tolerance on cheating and plagiarism. Any related offence will lead to disciplinary action including termination of studies at the University. Although cases of cheating or plagiarism are rare at the University, everyone should make himself / herself familiar with the content of the following website:
http://www.cuhk.edu.hk/policy/academichonesty/and thereby help avoid any practice that would not be acceptable.
Last updated: April 14, 2017 16:43:20