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  • Search: person:"Sakallioglu, Sadullah"
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Subject
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Multicollinearity 3 Autocorrelation 1 Biased regression 1 Estimation theory 1 Kleinste-Quadrate-Methode 1 Least squares method 1 Liu estimator 1 Mean square error matrix 1 Mean squared error 1 Multikollinearität 1 Multikolliniarität 1 Regression analysis 1 Regressionsanalyse 1 Ridge regression 1 Ridge regression estimator 1 Schätztheorie 1 Theorie 1 Theory 1 r − k Class estimator 1
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Article 4
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Article in journal 1 Aufsatz in Zeitschrift 1
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Undetermined 3 English 1
Author
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Kaçıranlar, Selahattin 3 Sakallıoğlu, Sadullah 3 Akdeniz, Fikri 1 Kaçiranlar, Selahattin 1 Sakallioglu, Sadullah 1 Styan, George P.H. 1 Werner, Hans Joachim 1 Şiray, Gülesen Üstündagˇ 1
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Statistical Papers / Springer 2 Sankhya / B : the Indian journal of statistics 1 Statistical papers 1
Source
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RePEc 2 ECONIS (ZBW) 1 OLC EcoSci 1
Showing 1 - 4 of 4
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r − k Class estimator in the linear regression model with correlated errors
Şiray, Gülesen Üstündagˇ; Kaçıranlar, Selahattin; … - In: Statistical Papers 55 (2014) 2, pp. 393-407
Autocorrelation in errors and multicollinearity among the regressors are serious problems in regression analysis. The aim of this paper is to examine multicollinearity and autocorrelation problems concurrently and to compare the r − k class estimator to the generalized least squares estimator,...
Persistent link: https://www.econbiz.de/10010998572
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A new biased estimator based on ridge estimation
Sakallıoğlu, Sadullah; Kaçıranlar, Selahattin - In: Statistical Papers 49 (2008) 4, pp. 669-689
Persistent link: https://www.econbiz.de/10008533751
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A new biased estimator based on ridge estimation
Sakallıoğlu, Sadullah; Kaçıranlar, Selahattin - In: Statistical papers 49 (2008) 4, pp. 669-689
Persistent link: https://www.econbiz.de/10003761745
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A NEW BIASED ESTIMATOR IN LINEAR REGRESSION AND A DETAILED ANALYSIS OF THE WIDELY-ANALYSED DATASET ON PORTLAND CEMENT
Kaçiranlar, Selahattin; Sakallioglu, Sadullah; … - In: Sankhya / B : the Indian journal of statistics 61 (1999) 3, pp. 443-459
Persistent link: https://www.econbiz.de/10006517315
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