A variation of multiple linear regression analysis for prediction of the occurrence or nonoccurrence of an event. To account for the nonnumerical nature of the predictand, a discriminant function is used as a type of regression function usually derived in such a way that positive values of the function correspond to “occurrence” and negative values to “nonoccurrence. ” In meteorology, for example, the occurrence of precipitation (the predictand) can be related to measures of vertical velocity, dewpoint temperature, pressure change, and other variables (the predictors) through a discriminant function. Values of the function above or below a threshold value (typically, zero) can be used to predict precipitation occurrence.