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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 Comparing The Most Commonly Used Classical Methods For Determining The Ridge Parameter In Ridge Regression(Journal of Selcuk University Natural and Applied Science, 2012) Sinan, Alper; Genç, AşırMulticollinearity is a most common problem in multiple regression models. Many different methods are developed to solve the problem of multicollinearity. Ridge regression estimation is a popular one of these methods. And the mostly investigated matter of this method is determining the ridge parameter; therefore, various procedures are developed for determining the ridge parameter in ridge regression. In this study, we compared the commonly used methods for choosing the ridge parameter in an actual data set taken from General Directorate of Turkish Highways and Turkish Statistical Institute. We calculated the ridge parameter by the methods which are known as ridge trace, ordinary ridge estimator and an iterative method for ordinary ridge estimator. We indicated the good and worst aspects of these methods in terms of mean square error (MSE), variance inflation factors (VIF) and the other multicollinearity statistics. According the results of this study, we found that, the ridge trace method is more useful then others when it is evaluated together with the statistics of model.Öğe Estimating Wind Speed In Black Sea Region With Panel Data Analysis(Journal of Selcuk University Natural and Applied Science, 2012) Atlı, Zeynep; Sinan, AlperPanel data analysis is a common method used especially in economic research and in other research in which time/unit relationship is significant. This study aims at predicting average wind speed during the years 2009-2010 in the cities of Sinop, Samsun, Ordu, Kastamonu, Bartın, Zonguldak and Karabük of Blacksea Region. In order to analyze the obtained data, of all panel data analysis methods, Random Effect Model and Fixed Effect Model have been used. Compatibility of these data sets have been compared via the use of graphics. The results have shown that Fixed Effect Model has turned out to be more effective in analyzing data according to units.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.Öğe Parçalı Regresyon Yardımı ile Bitki Boyu-Zaman İlişkisi Parametrelerinin Tahmini(Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2004) Karadavut, Ufuk; Genç, Aşır; Tozluca, Abdurrahman; Sinan, Alper; Karakoca, Aydın; Aksoyak, Şeref; Palta, ÇetinBu çalışma Bahri Dağdaş Uluslararası Tarımsal Araştırma Enstitüsü Deneme alanlarında yürütülmüştür. Çalışmada Dağdaş-94 buğday çeşiti kullanılmıştır. Bitkilerde lO'ar gün aralıklarla düzenli olarak 15 kez boy ölçümleri yapılmıştır. Her parselden 5 bitki tesadüfen alınmış ve üç tekrarlamalı olarak yapılan ölçümlerde, her ölçüm için toplam J 5 bitki kullanılmıştır. Buğday bitkisinin boyunun zamana göre modellenınesi ve model parametrelerinin tahmini uygulaına yönünden önem arzetmektedir. Bu amaçla, doğrusal olmayan bir model gösteren bitkinin boy uzunluğu ile zaman ilişkisi, belli noktalarda zıplamalar gösterirken bazı noktalarda kesilmeler gösterebilmektedir. Bu çalışmamızda buğday bitkisinin boy uzunluğu ve zaman ilişkisi açısından parçalı regresyon modelinin parametre tahmini ve zıplama noktalarının tahmin edilmesi ele alınmıştır.
