@article{Fakoor_Ajami_Amir Jahanshahi_Shariati_2020, title={A Density-Based Empirical Likelihood Ratio Approach for Goodness-of-fit Tests in Decreasing Densities}, volume={8}, url={http://iapress.org/index.php/soic/article/view/707}, DOI={10.19139/soic-2310-5070-707}, abstractNote={<p><span style="background-color: #ffffff;">In this paper, we propose a test for the null hypothesis that a decreasing density function belongs to a given<br>parametric family of distribution functions against the non-parametric alternative. This method, which is based on an empirical likelihood (EL) ratio statistic, is similar to the test introduced by Vexler and Gurevich [23]. The consistency of the test statistic proposed is derived under the null and alternative hypotheses. A simulation study is conducted to inspect the power of the proposed test under various decreasing alternatives. In each scenario, the critical region of the test is obtained using a Monte Carlo technique. The applicability of the proposed test in practice is demonstrated through a few real data examples.</span></p> <p>&nbsp;</p&gt;}, number={1}, journal={Statistics, Optimization & Information Computing}, author={Fakoor, Vahid and Ajami, Masoud and Amir Jahanshahi, Seyed Mahdi and Shariati, Ali}, year={2020}, month={Feb.}, pages={66-79} }