Results 191 to 200 of about 11,350 (238)
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Communications in Statistics Part B: Simulation and Computation, 2013
It is known that multicollinearity inflates the variance of the maximum likelihood estimator in logistic regression. Especially, if the primary interest is in the coefficients, the impact of collinearity can be very serious. To deal with collinearity, a ridge estimator was proposed by Schaefer et al. The primary interest of this article is to introduce
Deniz Inan
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It is known that multicollinearity inflates the variance of the maximum likelihood estimator in logistic regression. Especially, if the primary interest is in the coefficients, the impact of collinearity can be very serious. To deal with collinearity, a ridge estimator was proposed by Schaefer et al. The primary interest of this article is to introduce
Deniz Inan
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Liu-Type Multinomial Logistic Estimator
Sankhya B, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mohamed R Abonazel, Abonazel Mohamed R
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Efficiency of the modified jackknifed Liu-type estimator
Statistical Papers, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Esra Akdeniz
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Using Liu-Type Estimator to Combat Collinearity
Communications in Statistics - Theory and Methods, 2003Linear regression model and least squares method are widely used in many fields of natural and social sciences. In the presence of collinearity, the least squares estimator is unstable and often gives misleading information. Ridge regression is the most common method to overcome this problem.
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The distribution of stochastic shrinkage biasing parameters of the Liu type estimator
Applied Mathematics and Computation, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Akdeniz F., Öztürk F.
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More on Liu-Type Estimator in Linear Regression
Communications in Statistics - Theory and Methods, 2004Abstract Recently, Liu [Liu, K. (2003). Using Liu-type estimator to combat collinearity. Commun. Statist. Theory Methods 32:1009–1020] introduced the Liu-type estimator to combat collinearity in linear regression. The Liu-type estimator can be applied in two ways. First, when the effect of collinearity is moderate, the Liu-type estimator can be used as
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Robust Liu‐type estimator based on GM estimator
Statistica Neerlandica, 2023Ordinary Least Squares Estimator (OLSE) is widely used to estimate parameters in regression analysis. In practice, the assumptions of regression analysis are often not met. The most common problems that break these assumptions are outliers and multicollinearity problems. As a result of these problems, OLSE loses efficiency.
Melike Işılar, Y. Murat Bulut
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Inverse Gaussian Liu-type estimator
Communications in Statistics - Simulation and Computation, 2021The inverse Gaussian regression (IGR) model parameters are generally estimated using the maximum likelihood (ML) estimation method.
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