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A new entropy estimator and its application to goodness of fit test for Weibull distribution | ||
| Journal of Mahani Mathematical Research | ||
| دوره 14، شماره 2 - شماره پیاپی 32، مرداد 2025، صفحه 1-19 اصل مقاله (477.63 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22103/jmmr.2024.22859.1573 | ||
| نویسندگان | ||
| Sayed Qasim Alavi؛ Hadi Alizadeh Noughabi* ؛ Sarah Jomhoori | ||
| Department of Statistics, University of Birjand, Birjand, Iran | ||
| چکیده | ||
| In this article, we introduce a new estimator of entropy of continuous random variable. Bias, variance and the mean squared error of the new estimator are obtained and compared with the other existing estimators. The results show that the proposed estimator has a lower mean squared error than its competitors. Then, we propose some goodness of fit tests for Weibull distribution based on the entropy estimators. To assess the effectiveness of the proposed tests, we utilize Monte Carlo simulation to evaluate their power against eighteen different alternatives with varying sample sizes. The results show that the tests are powerful and we can use them in practice. Finally, two real datasets are considered and modeled by the Weibull distribution. | ||
| کلیدواژه‌ها | ||
| Entropy estimator؛ Weibull distribution؛ Monte Carlo simulation؛ Critical points؛ Power of the test | ||
| مراجع | ||
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