Simulation of Dynamic Models

Most of the statistical methods presented in the previous chapters deal with inherently static data. With the exception of a few time-series examples, there is rarely a time component involved and typically observed random variables or vectors are assumed independent. We now move on to a different setting that involves a time component and/or dependent random variables. In general, such models are called “dynamic” as they describe changes over time or space. A consequence of dynamic behavior is dependence between random variables at different points in time or space.