http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
From comparison density to two sample analysis
"Texas A & M Research Foundation, Project Number 5641."
"Parzen (1979) argues that statistical data analysis should be defined as fitting probability models to data. This paper presents typical concepts and recent results of our modeling theory which emphasizes quantile domain functions, information measures, and comparison density estimation. Ultimate goals include: unify parametric and nonparametric inference for continuous and discrete data; demonstrate that mathematical statistical and data analytic approaches are both needed for statistical inference; stimulate exoteric methods (applicable by applied researchers) rather than esoteric methods (known only to a small group of mathematical statisticians); combine mathematical statistical and data analytic views to develop methods of statistical analysis which are based on assumptions (known model) which are tested in ways that provide insight how to model deviations of the data from the assumed model (and thus identify a "true" model as an "iterated" model)."--Leaf 1.
Includes bibliographical references (leaf 18).
Sponsored by the U.S. Army Research Office
Minimum information parameter estimation
Technical report (Texas A & M University. Department of Statistics) ; no. 169