Abstract
Using a generalization of the divergence of degree λ on the location model, a distance between two populations is proposed for mixed data of categorical and continuous variables. Three propositions about the proposed distance are derived from properties of the divergence. Two real examples and some numerical examples are given in order to study the propositions in detail and have a suitable value of λ. The information of degree λ is considered as the distance between an observation and a population, and minimizing this distance establishes an allocation rule on the location model. The allocation rule is shown to be equivalent to the optimal rule based on the maximum-likelihood method.
