المقارنة بين طريقتي Sو Mلتقدير انحدار الحرف الحصين في ظل وجود القيم الشاذة باستعمال أسلوب المحاكاة

Muntaha Dakhel, Tariq Aziz
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引用次数: 0

摘要

通常,统计方法是基于回归模型数据的概率分布为正态分布的假设,但在实际应用中,由于一些异常值的存在,这些数据往往具有其他分布或可能偏斜。本研究采用两种方法估计海马回归模型的参数。如果使用文字回归来解决多重共线性问题,使用强大的方法,即(M, S)来显示观测值中异常值存在的影响,如果使用基于包含两个自变量的模型的模拟方法。为了对这些方法进行比较,指出采用AMSE均方误差比较测度来衡量模型效率的最佳估计方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
المقارنة بين طريقتي Sو Mلتقدير انحدار الحرف الحصين في ظل وجود القيم الشاذة باستعمال أسلوب المحاكاة
Mostly, statistical methods are based on the assumption that the probability distribution of regression model data is normal, but in the applied case, these data often have other distributions or may be skewed, due to the presence of some outliers.In this research, two methods were used to estimate the parameters of the hippocampal regression model. If literal regression is used to address the problem of multicollinearity using powerful methods, namely (M, S) to show the effect of the presence of outliers in observation values, if a simulation method is used based on a model that includes two independent variables. In order to make a comparison between these methods and indicate the best estimation method using AMSE mean square error comparison measure to measure model efficiency.
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