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Modeling the Log Density Distribution with Orthogonal Polynomials

Abstract

Eugene Demidenko

A possibly multimodal log density is modeled via orthogonal polynomials. An efficient Fisher scoring algorithm for maximum likelihood density estimation is described. Statistical hypothesis testing is emphasized such as the test for normality and density multimodality. The density estimation is illustrated with two biomedical examples: brain oxygen distribution and toenail arsenic distribution among New Hampshire residents.

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