Results 231 to 240 of about 2,495,910 (283)
COMBINING THE LIU ESTIMATOR AND THE PRINCIPAL COMPONENT REGRESSION ESTIMATOR
Communications in Statistics - Theory and Methods, 2001 In this paper we introduce a class of estimators which includes the ordinary least squares (OLS), the principal components regression (PCR) and the Liu estimator [1]. In particular, we show that our new estimator is superior, in the scalar mean-squared error (mse) sense, to the Liu estimator, to the OLS estimator and to the PCR estimator.
Sadullah Sakallioğlu +1 more
exaly +3 more sources
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
exaly +4 more sources
On the almost unbiased generalized liu estimator and unbiased estimation of the bias and mse
Communications in Statistics - Theory and Methods, 1995 In this paper, we derive the almost unbiased generalized Liu estimator and examine an exact unbiased estimator of the bias and mean squared error of the feasible generalized Liu estimator . We compare the almost unbiased generalized Liu estimator (AUGLE) with the generalized Liu estimator (GLE) and with the ordinary least squares estimator (OLSE).
Selahattin Kaçıranlar
exaly +5 more sources
Inverse Gaussian Liu-type estimator
Communications in Statistics - Simulation and Computation, 2021 The inverse Gaussian regression (IGR) model parameters are generally estimated using the maximum likelihood (ML) estimation method.
Bulut, YAKUP MURAT, Y. Murat Bulut
openaire +4 more sources
A robust Liu regression estimator
Communications in Statistics - Simulation and Computation, 2017 The least-squares regression estimator can be very sensitive in the presence of multicollinearity and outliers in the data. We introduce a new robust estimator based on the MM estimator.
Peter Filzmoser, Fatma Sevinç Kurnaz
openaire +4 more sources
On the Restricted Liu Estimator in the Logistic Regression Model
Communications in Statistics - Simulation and Computation, 2014 The logistic regression model is used when the response variables are dichotomous. In the presence of multicollinearity, the variance of the maximum likelihood estimator (MLE) becomes inflated. The Liu estimator for the linear regression model is proposed by Liu to remedy this problem. Urgan and Tez and Mansson et al.
Gülesen Üstündag Siray +2 more
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Robust Liu-type estimator for regression based on M-estimator
Communications in Statistics - Simulation and Computation, 2015 ABSTRACTThe problem of multicollinearity and outliers in the dataset can strongly distort ordinary least-square estimates and lead to unreliable results. We propose a new Robust Liu-type M-estimator to cope with this combined problem of multicollinearity and outliers in the y-direction.
Hasan Ertas +2 more
openaire +2 more sources