  Recent studies in the literature have introduced a new approach to earthquake
forecasting based on representing the space-time patterns of localized
seismicity by a time-dependent system state vector in a real-valued Hilbert
space and deducing information about future space-time fluctuations from the
phase angle of the state vector. While the success rate of this Pattern
Informatics (PI) method has been encouraging, the method is still in its
infancy. Procedural analysis, statistical testing, parameter sensitivity
investigation and optimization all still need to be performed. In this paper,
we attempt to optimize the PI approach by developing quantitative values for
"predictive goodness" and analyzing possible variations in the proposed
procedure. In addition, we attempt to quantify the systematic dependence on the
quality of the input catalog of historic data and develop methods for combining
catalogs from regions of different seismic rates.
