Asymptotic Distribution of Probabilities of Misclassification for Edgeworth Series Distribution (ESD)
Author(s) -
Awogbemi Clement Adeyeye
Publication year - 2020
Publication title -
engineering mathematics
Language(s) - English
Resource type - Journals
eISSN - 2640-088X
pISSN - 2640-0855
DOI - 10.11648/j.engmath.20200401.11
Subject(s) - edgeworth series , series (stratigraphy) , statistics , mathematics , multivariate normal distribution , distribution (mathematics) , inverse chi squared distribution , multivariate statistics , variance (accounting) , normal distribution , expression (computer science) , probability distribution , distribution fitting , computer science , mathematical analysis , paleontology , accounting , business , biology , programming language
The exact distribution of the test statistics in multivariate case is quite complicated in many situations, even when the underlying distribution is multivariate normal. This is due to the complex nature of the expression and therefore, there is a need to derive the asymptotic expression for the distribution. In this study, the asymptotic distribution of errors of misclassification for Edgeworth Series is derived by using Taylor’s expansion. The error of misclassification for the conditional probability of misclassification was expanded around the means emanating from populations one and two using approximated mean and variance of the errors of misclassification. The distribution of error of misclassification of the conditional probability of misclassification for ESD is approximately normal with mean zero and variance one.
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