On a Construction of Markov Models in Continuous Time

Abstract

This paper studies a novel idea for constructing continuous-time stationary Markov models. The approach undertaken is based on a latent representation of the corresponding transition probabilities that conveys to appealing ways to study and simulate the dynamics of the constructed processes. Some well-known models are shown to fall within this construction shedding some light on both theoretical and applied properties. As an illustration of the capabilities of our proposal a simple estimation problem is posed.Gibbs sampler; Markov process; Stationary process