High-order Markov chain models extend the conventional framework by incorporating dependencies that span several previous states rather than solely the immediate past. This extension allows for a ...

This paper considers Markov error-correction (MEC) models in which deviations from the long-run equilibrium are characterized by different rates of adjustment. To motivate our analysis and illustrate ...

Discrete-time hidden Markov models are a broadly useful class of latent variable models with applications in areas such as speech recognition, bioinformatics, and climate data analysis. It is common ...

Until recently, Markov models and analytical methods were fairly obscure mathematical techniques rarely applied outside of academic settings. The advent of functional safety standards, particularly ...