where "1A" is the indicator function which takes on the value one when the event "A" occurs, and zero otherwise: in this formulation, for any given observation "yi", only one of the two terms inside the product contributes, according to whether "yi"=0 or 1. The likelihood function is more fully specified by defining the formal parameters "μi" as parameterised functions of the explanatory variables: this defines the likelihood in terms of a much reduced number of parameters. Fitting of the model is usually achieved by employing the method of maximum likelihood to determine these parameters. In practice, the use of a formulation as a generalised linear model allows advantage to be taken of certain algorithmic ideas which are applicable across the whole class of more general models but which do not apply to all maximum likelihood problems.