MAGIC093: Markov Processes

Course details

A core MAGIC course

Semester

Spring 2025
Monday, January 27th to Friday, April 4th

Hours

Live lecture hours
20
Recorded lecture hours
0
Total advised study hours
80

Timetable

Tuesdays
11:05 - 11:55 (UK)
Thursdays
12:05 - 12:55 (UK)

Course forum

Visit the https://maths-magic.ac.uk/forums/magic093-markov-processes

Description

Markov processes in discrete and continuous time will be presented for finite and countable state spaces in discrete time, as well as for some basic processes in continuous time. Standard material will include state classification, the (strong) Markov property, and ergodicity. A bit more advanced material could include coupling and recurrence applied to convergence rates. Some attention will also be paid to the applicability of Markov processes in a variety of fields such as economics, operational research, biology, statistics, and physics. 

Prerequisites

Some basic knowledge about Markov chains is highly desirable. 

Syllabus

1. Discrete-time Markov chains on countable state spaces;
1a Existence
1b Classification of states
1c Ergodic theory
2. Poisson processes
3. Continuous-time Markov chains on countable state spaces;
3a Construction
3b Backward and forward equations
3c Classification of states
3d Ergodic theory
4 Applications

Lecturer

  • JT

    Professor Jacco Thijssen

    University
    University of York

Bibliography

No bibliography has been specified for this course.

Assessment

The assessment for this course will be released on Tuesday 22nd April 2025 at 00:00 and is due in before Friday 2nd May 2025 at 11:00.

Assessment for all MAGIC courses is via take-home exam which will be made available at the release date (the start of the exam period).

You will need to upload a PDF file with your own attempted solutions by the due date (the end of the exam period).

If you have kept up-to-date with the course, the expectation is it should take at most 3 hours’ work to attain the pass mark, which is 50%.

Please note that you are not registered for assessment on this course.

Files

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Lectures

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