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首页> 外文期刊>Journal of Mathematics and Statistics >A COMPARISON BETWEEN CLASSICAL AND ROBUST METHOD IN A FACTORIAL DESIGN IN THE PRESENCE OF OUTLIER | Science Publications
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A COMPARISON BETWEEN CLASSICAL AND ROBUST METHOD IN A FACTORIAL DESIGN IN THE PRESENCE OF OUTLIER | Science Publications

机译：存在局外人设计中经典与鲁棒方法的比较|查阅全文需要付费。科学出版物

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> Analysis of Variance (ANOVA) techniques which is based on classical Least Squares (LS) method requires several assumptions, such as normality, constant variances and independency. Those assumptions can be violated due to several causes, such as the presence of an outlying observation. There are many evident in literatures that the LS estimate is easily affected by outliers. To remedy this problem, a robust procedure that provides estimation, inference and testing that are not influenced by outlying observations is put forward. A well-known approach to handle dataset with outliers is the M-estimation. In this study, both classical and robust procedures are employed to data of a factorial experiment. The results signify that the classical method of least squares estimates instead of robust methods lead to misleading conclusion of the analysis in factorial designs.
机译： >基于经典最小二乘（LS）方法的方差分析（ANOVA）技术需要一些假设，例如正态性，恒定方差和独立性。可能由于多种原因而违反这些假设，例如存在异常的观察结果。文献中有很多证据表明，最小二乘估计很容易受到异常值的影响。为了解决这个问题，提出了一种鲁棒的程序，该程序提供不受外界观测影响的估计，推断和测试。 M估计是一种处理带有异常值的数据集的著名方法。在这项研究中，经典和鲁棒的程序都用于阶乘实验的数据。结果表明，最小二乘估计的经典方法而不是鲁棒方法导致了析因设计中分析的误导性结论。

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