:: Volume 13, Issue 1 (9-2016) ::
JSRI 2016, 13(1): 1-24 Back to browse issues page
Testing Skew-Laplace Distribution Using Density-based Empirical Likelihood Approach
M. Safavinejad *1, S. Jomhoori, H. Alizadeh Noughabi
1- , m_safavinejad1368@yahoo.com
Abstract:   (3795 Views)

Abstract: In this paper, we first describe the skew-Laplace distribution and its properties. We then introduce a goodness of fit test for this distribution according to the density-based empirical likelihood ratio concept. Asymptotic consistency of the proposed test is demonstrated.

The critical values and Type I error of the test are obtained by Monte Carlo simulations.

Moreover, the empirical distribution function (EDF) tests are considered for the skew-Laplace distribution to show they do not have acceptable Type I error in comparison with the proposed test. Results show that the proposed test has an excellent Type I error which does not depend on the unknown parameters.

The results obtained from simulation studies designed to investigate the power of the test are presented, too. The applicability of the proposed test in practice is demonstrated by real data examples.

Keywords: Density-based empirical likelihood, likelihood ratio, skew-Laplace distribution, goodness of fit tests, Type I error.
Full-Text [PDF 212 kb]   (1098 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/11/23 | Accepted: 2016/11/23 | Published: 2016/11/23

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Volume 13, Issue 1 (9-2016) Back to browse issues page