ENTROPY MINIMAX MULTIVARIATE STATISTICAL MODELING—II: APPLICATIONS

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Abstract
Applications of entropy minimax are summarized in three major areas: meteorology, engineering/ materials science, and medicine/biology. The applications cover both discrete patterns in multidimensional spaces of mixed quantitative and qualitative variables, and continuous patterns employing concepts of potential functions and fuzzy entropies. Major achievements of entropy minimax modeling include the first long range weather forecasting models with statistical reliability significantly above chance verified on independent data, the first models of fission gas release and nuclear fuel failure under commercial operating conditions with significant and independently verified statistical reliability, and the first prognosis models in coronary artery disease and in non-Hodgkin's lymphoma with significant predictability verified on independent data. In addition, applications of entropy minimization and maximization separately are reviewed, including feature selection, unsupervised classification, probability estimation, statistical distribution determination, statistical mechanics and thermodynamics, pattern recognition, spectral analysis and image reconstruction. Comparisons between entropy minimax and other methodolodies are provided, including sample average predictors, nearest neighbors predictors, linear regression, logistic regression, Cox proportional hazards regression, recursive partitioning, linear discriminant analysis, mechanistic modeling, and expert (heuristic) programming.