A Comparison of WK3and MSE for Regression Model Fitting

Wasfi Taher, Kahwachi
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Abstract

Wasfi Kahwachi4 (WK4) measurement is considered as one of the powerful statistical tools to testing goodness of fit of regression model when compared with the MSE (Mean Squared Error) measure. In this paper, the main goal is to detect the best measure for model fitting by using a comparison between MSE and WK4 measure. This new measure (WK4) applied on five samples to compare its value with MSE value which obtained from the same samples to judge on the new criterion for fitting the models. The results showed that the WK4 measure was better than the MSE measure (smaller) for fitting regression model in all samples. This gives the conclusion that Wk4 can be used besides MSE for testing goodness of fit in regression analysis.
回归模型拟合wk3与MSE的比较
Wasfi Kahwachi4 (WK4)测度被认为是检验回归模型拟合优度的有力统计工具之一,与均方误差(MSE)测度相比。在本文中,主要目标是通过比较MSE和WK4度量来检测模型拟合的最佳度量。该新测度(WK4)应用于5个样本,将其值与相同样本的MSE值进行比较,以判断模型拟合的新准则。结果表明,在所有样本中,WK4测度都比MSE测度(较小)更适合拟合回归模型。这就得出了Wk4可以在MSE之外用于检验回归分析的拟合优度的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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