A Decision Theory Approach to the Approximation of Discrete Probability Densities
Dimitri Kazakos, Theodore Cotsidas · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1980
The problem of approximating a probability density function by a simpler one is considered from a decision theory viewpoint. Among the family of candidate approximating densities, we seek the one that is most difficult to discriminate from the original. This formulation leads naturaliy to the density at the smallest Bhattacharyya distance. The resulting optimization problem is analyzed in detail.