Path integrals for continuous-time Markov chains

Path Integrals for Continuous-Time Markov Chains

This note presents a method of evaluating the distribution of a path integral for Markov chains on a countable state space. We illustrate the method with reference to several models, including birth-death processes and the birth, death and catastrophe process.

Integrals for continuous-time Markov chains.

This paper presents a method of evaluating the expected value of a path integral for a general Markov chain on a countable state space. We illustrate the method with reference to several models, including birth-death processes and the birth, death and catastrophe process.

Continuous Time Markov Chains

Discrete-time Markov chains are useful in simulation, since updating algorithms are easier to construct in discrete steps. They can also be useful as crude models of physical, biological, and social processes. However, in the physical and biological worlds time runs continuously, and so discrete-time mathematical models are not always appropriate. This is especially true in population biology –...

Continuous-time Markov Chains

Continuous-time homogeneous Markov chains