Unification of Statistical Methods for Continuous and Discrete Data
We propose the concept of unification of statistical methods in order to develop a general philosophy of statistical data analysis. We propose that ways of thinking about statistical ends (goals) and means (procedures) are needed that provide a framework for implementing and comparing several different approaches to a data analysis problem. We believe that unification has benefits which include: existing (often parametric) methods will be better understood; many new (often nonparametric) methods will be developed. The new methods are usually computer intensive; consequently unification of statistical methods can be considered to be closely related to computational statistics. We define computational statistical methods as characterized by being graphics intensive and number crunching intensive.
KeywordsQuantile Function Quadratic Detector Comparison Density Linear Rank Statistic Parametric Probability Model
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