Time-series are often modelled probabilistically as sequences of segments using first-order Markovian hidden variables representing different dynamics regimes. Such dynamics-regime variables implicitly define a geometric segment-duration distribution. A more flexible distribution requires introducing extra variables into the model with increased computational cost. This can be achieved in different ways, whose properties and categorization are still unclear. This book describes in a simple way different approaches to modelling the segment-duration distribution by categorizing them into three...