Divided Populations and Stochastic Models
The title of this entry requires some explanation. I use the term ‘stochastic models’ to distinguish those theoretical models which include one or more stochastic variables from ‘determinist models’ which do not. I shall confine attention to some stochastic models which are obtained by introducing into a determinist model a single stochastic variable (which can be multivariate, but will in illustrative examples be univariate). I shall use the term ‘generating system’ to mean a determinist model in which from an initial state of the system an unending sequence of successive states of the system can be exactly predicted by means of a set of rules such as lagged equations. It is convenient to distinguish generating systems from stochastic models rather than extend the former class to include some or all of the latter. The important feature of stochastic models is that they can make allowance for wide margins of uncertainty and ignorance.