A method for allocating an individual to the correct population group given an existing sample of individuals from the groups. The basis of discriminatory analysis is a rule that allocates the individual to the correct group with minimal probability of misclassification. In linear discriminatory analysis m linear discriminatory functions are defined for m categories. Each function is a linear combination of variables, or attributes, that are used to discriminate between the observations. The coefficients for each function are estimated based on a sample of past observations called the training set. To assign a new observation to one of these categories the values of each of the m discriminatory functions are evaluated, given the attributes associated with this observation, and the category is chosen for which the value of the discriminatory function is the highest.