:: Volume 12, Issue 1 (9-2018) ::
JSS 2018, 12(1): 119-141 Back to browse issues page
Robust Analysis of Variance based on Permutation Distribution of Trimmed Mean
Kourosh Dadkhah * , Edris Samadi Tudar
Abstract:   (5637 Views)

The presence of outliers in data set may affect structure of analysis of variance test so that test results led to wrong acceptance or rejection of null hypothesis. In this paper the method of robust permutation distribution of F statistic based on trimmed mean is proposed. This method by permutation distribution of a function of trimmed mean, reduces the sensitivity to classical assumptions such as normality and presence of outlier and it guarantees the reliability of result. The proposed method is compared with robust analysis of variance based of forward search approach. The proposed method, unlike the forward search-based approach is free of restricted parametric assumptions and computationally spend less time. Numerically assessment results on type I error and power of test, demonstrate good performance of this robust method in comparison with competitor method.

Keywords: Analysis of Variance, Robustness, Outlier, Permutation Distribution, Forward Search.
Full-Text [PDF 236 kb]   (1987 Downloads)    
Type of Study: Applied | Subject: Applied Statistics
Received: 2016/05/22 | Accepted: 2017/08/24 | Published: 2018/04/22



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Volume 12, Issue 1 (9-2018) Back to browse issues page