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Atan regularized for the high dimensional Poisson regression model | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، Special Issue، اسفند 2021، صفحه 2197-2202 اصل مقاله (857.22 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.6092 | ||
| نویسندگان | ||
| Ali Hameed Yousif* 1؛ Ahlam Hanash Gatea2 | ||
| 1College of Administration and Economic, Wasit University, Iraq | ||
| 2College of Languages, University of Baghdad, Iraq | ||
| تاریخ دریافت: 10 مهر 1400، تاریخ بازنگری: 30 آبان 1400، تاریخ پذیرش: 17 آذر 1400 | ||
| چکیده | ||
| Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection. | ||
| کلیدواژه‌ها | ||
| Poisson regression؛ Lasso؛ Adaptive Lasso؛ Atan | ||
| مراجع | ||
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