TEZ8285Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2011.Kaynakça (s. 107-111) var.xiii, 113 s. : res., çizelge ; 29 cm.In multiple linear regression; ordinary least squares analysis does not give satisfactory and consistent results in the presence of linear depency among predictors (multicollinearity) and existence of outliers in data. In the literature, several biased estimator have been proposed as alternatives to the least squares estimator in the presence of multicollinearity to mitigate the effect of multicollinearity in the analysis. A class that includes a part of biased estimator has been proposed by Lee and Birch (1988). After that, it was shown that Liu and generalized Liu estimators can also be included in this class by ...
Abstract: An outlier is an observation that deviates markedly from the majority of the data. To know...
TEZ12440Tez (Doktora) -- Çukurova Üniversitesi, Adana, 2016.Kaynakça (s.) var.XI, 148 s. :_res. (gnl...
The problem of multicollinearity and outliers in the dataset can strongly distort ordinary least-squ...
The ordinary least squares (OLS) method is the most commonly used method in multiple linear regressi...
Consider the regression model y = ß01 + Xß + ?. Recently, the Liu estimator, which is an alternative...
TEZ8991Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2011.Kaynakça (s. 63-66) var.xiii, 67 s....
TEZ7639Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2009.Kaynakça (s.55-58) var.ix, 69 s. ; ...
Abstract This paper describes a procedure for identifying multiple outliers in linear regression. Th...
In multiple linear regression analysis, multicollinearity and outliers are two main problems. When m...
Regression analysis is one of the most important branches of multivariate statistical techniques. It...
In the multiple linear regression analysis, the ridge regression estimator is often used to address ...
In the multiple linear regression analysis, the ridge regression estimator is often used to address ...
TEZ6479Tez (Doktora) -- Çukurova Üniversitesi, Adana, 2007.Kaynakça (s.90-95) var.ix, 96 s. ; 29 cm....
This paper introduces a new biased estimator, namely, almost unbiased Liu estimator (AULE) of β...
In the presence of collinearity certain biased estimation procedures like ridge regression, generali...
Abstract: An outlier is an observation that deviates markedly from the majority of the data. To know...
TEZ12440Tez (Doktora) -- Çukurova Üniversitesi, Adana, 2016.Kaynakça (s.) var.XI, 148 s. :_res. (gnl...
The problem of multicollinearity and outliers in the dataset can strongly distort ordinary least-squ...
The ordinary least squares (OLS) method is the most commonly used method in multiple linear regressi...
Consider the regression model y = ß01 + Xß + ?. Recently, the Liu estimator, which is an alternative...
TEZ8991Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2011.Kaynakça (s. 63-66) var.xiii, 67 s....
TEZ7639Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2009.Kaynakça (s.55-58) var.ix, 69 s. ; ...
Abstract This paper describes a procedure for identifying multiple outliers in linear regression. Th...
In multiple linear regression analysis, multicollinearity and outliers are two main problems. When m...
Regression analysis is one of the most important branches of multivariate statistical techniques. It...
In the multiple linear regression analysis, the ridge regression estimator is often used to address ...
In the multiple linear regression analysis, the ridge regression estimator is often used to address ...
TEZ6479Tez (Doktora) -- Çukurova Üniversitesi, Adana, 2007.Kaynakça (s.90-95) var.ix, 96 s. ; 29 cm....
This paper introduces a new biased estimator, namely, almost unbiased Liu estimator (AULE) of β...
In the presence of collinearity certain biased estimation procedures like ridge regression, generali...
Abstract: An outlier is an observation that deviates markedly from the majority of the data. To know...
TEZ12440Tez (Doktora) -- Çukurova Üniversitesi, Adana, 2016.Kaynakça (s.) var.XI, 148 s. :_res. (gnl...
The problem of multicollinearity and outliers in the dataset can strongly distort ordinary least-squ...