The Markov Property
The Markov Property
A time series of random variables, $X_1, X_2, X_3, \dots$, is said to be a Markov chain if it has the following property: $$ P(X_t=x_t|X_0=x_0,X_1=x_1,\dots,X_{t-1}=x_{t-1}) = P(X_t=x_t|X_{t-1}=x_{t-1}) $$
Syllabus Aims
- You should be able to write out the definition of the Markov property.
- You should be able to explain why the Markov property ensures that we can represent a Markov chain using a transition graph.
- You should be able to interpret the elements of the transition probability matrix by making reference to the Markov property.
Description and link | Module | Author | ||
| Introductory notes on Markov chains and the Markov property. | SOR3012 | J. F. McCann |
Description and link | Module | Author | ||
| Introduction to the Markov property | SOR3012 | G. Tribello |
Contact Details
School of Mathematics and Physics,
Queen's University Belfast,
Belfast,
BT7 1NN
Email: g.tribello@qub.ac.uk
Website: mywebsite