Abstract
This paper presents a pattern analysis technique that has been successfully applied to a set of hydrometric network data collected in British Columbia, Canada. This technique can extract information from a set of observed heterogeneous multivariate data. The data are represented as n-tuples of mixed discrete and continuous values. The technique is capable of screening out statistically irrelevant information. It is also able to detect inherent subgroups in the data through adopting an event-covering approach. The subgroup characteristics represent important empirical understanding even though there may be considerable probabilistic variation within each individual subgroup.
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