Jackknife empirical likelihood ratio test for log symmetric distribution using probability weighted moments

2024/10/05 by S, Anjana, Kattumannil, Sudheesh
#FOS: Computer and information sciences #FOS: Mathematics #Methodology (stat.ME) #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.2410.04082

Abstract

Log symmetric distributions are useful in modeling data which show high skewness and have found applications in various fields. Using a recent characterization for log symmetric distributions, we propose a goodness of fit test for testing log symmetry. The asymptotic distributions of the test statistics under both null and alternate distributions are obtained. As the normal-based test is difficult to implement, we also propose a jackknife empirical likelihood (JEL) ratio test for testing log symmetry. We conduct a Monte Carlo Simulation to evaluate the performance of the JEL ratio test. Finally, we illustrated our methodology using different data sets.

Related

• On testing the class of symmetry using entropy characterization and empirical likelihood approach
• Jackknife empirical likelihood ratio test for testing the equality of semivariance
• Jackknife empirical likelihood based inference for Probability weighted moments
• Jackknife Empirical Likelihood Ratio Test for Cauchy Distribution
• Small-sample testing inference in symmetric and log-symmetric linear regression models