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L. Al-Labadi

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Preprint Oct 2026

Goodness-of-Fit Tests via Kernel Density Estimation: Univariate and Multivariate Approaches

This paper introduces goodness-of-fit tests based on leave-one-out kernel density estimation (KDE) for both univariate and multivariate data. The proposed test statistic takes the form of a log-likelihood ratio comparing a parametric null model with a nonparametric KDE-based estimator, where the leave-one-out construct...

L. Al-Labadi, A. Alzaatreh, Ruo-Die Yu et al. · 0 citations

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