  We address classification of distributional data, where units are described
by histogram or interval-valued variables. The proposed approach uses a linear
discriminant function where distributions or intervals are represented by
quantile functions, under specific assumptions. This discriminant function
allows defining a score for each unit, in the form of a quantile function,
which is used to classify the units in two a priori groups, using the Mallows
distance. There is a diversity of application areas for the proposed linear
discriminant method. In this work we classify the airline companies operating
in NY airports based on air time and arrival/departure delays, using a full
year fights.
