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Öğe A useful approach to identify the multicollinearity in the presence of outliers(Taylor & Francis Ltd, 2015) Sinan, Alper; Alkan, B. BarisThe presence of outliers in the data sets affects the structure of multicollinearity which arises from a high degree of correlation between explanatory variables in a linear regression analysis. This affect could be seen as an increase or decrease in the diagnostics used to determine multicollinearity. Thus, the cases of outliers reduce the reliability of diagnostics such as variance inflation factors, condition numbers and variance decomposition proportions. In this study, we propose to use a robust estimation of the correlation matrix obtained by the minimum covariance determinant method to determine the diagnostics of multicollinearity in the presence of outliers. As a result, the present paper demonstrates that the diagnostics of multicollinearity obtained by the robust estimation of the correlation matrix are more reliable in the presence of outliers.Öğe Bakla (Victia Faba L.) Bitkilerinin Tohumlarında Çıkışa Kadar Geçen Süredeki Nem Miktarları Değişiminin İstatistiksel Analizi(Afyon Kocatepe Üniversitesi Fen Bilimleri Dergisi, 2005) Genç, Aşır; Karadavut, Ufuk; Karakoca, Aydın; Sinan, Alper[Abstract Not Available]Öğe New Parameters for Nuclear Charge Radius Formulas(Acta Physica Polonica B, 2013) Bayram, Tuncay; Akkoyun, Serkan; Kara, Seyit Okan; Sinan, AlperParameters of widely used nuclear rms charge radius formulas have been refitted based on the latest experimental data for about 900 nuclei. It has been seen that the new parameters in the formulas give better results than the previous ones. Besides, an N1?3-dependent formula has been proposed and discussed. This formula gives effective results for rms charge radius. The standard deviation in all formulas with new parameters are concentrated between ?0.1 and 0.1. In other words, for about 90% of nuclei, the differences of charge radii from experimental values are lower than 0.1 fm.












