Document Type

Article

Publication Title

Journal of Data Science

Publication Date

10-2012

Volume

10

Issue

4

Disciplines

Mathematics

Abstract

Correlation coefficients are generally viewed as summaries, causing them to be underutilized. Creating functions from them leads to their use in diverse areas of statistics. Because there are many correlation coefficients (see, for example, Gideon (2007)) this extension makes possible a very broad range of statistical estimators that rivals least squares. The whole area could be called a "Correlation Estimation System." This paper outlines some of the numerous possibilities for using the system and gives some illustrative examples. Detailed explanations are developed in earlier papers. The formulae to make possible both the estimation and some of the computer coding to implement it are given. This approach has been taken in hopes that this condensed version of the work will make the ideas accessible, show their practicality, and promote further developments.

Keywords

Classical regression, correlation coefficient, density parameter estimation, nonlinear regression, rank statistics

Rights

© 2012 Rudy Gideon

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