ABSTRACT
There are two rather different approaches to constructing a Markov chain. The first is through the transition laws of the chain. The second is through the use of iterating functions. This is particularly suited to the use of Markov chains in a time series context, where we wish to construct sample paths of the chain in an explicit manner rather than work with the distributions of the chain. This can also be carried out in a great degree of generality.
