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Journal of New Theory, 2022 The sensitivity of the least-squares estimation in a regression model is impacted by multicollinearity and autocorrelation problems. To deal with the multicollinearity, Ridge, Liu, and Ridge-type biased estimators have been presented in the statistical ...
Tuğba Söküt Açar
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Statistical Papers, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kurnaz, Fatma Sevinc, Akay, Kadri Ulas
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A New Biased Estimator Derived from Principal Component Regression Estimator [PDF]
, 2010 A new biased estimator obtained by combining the Principal Component Regression Estimator and the special case of Liu-type estimator is proposed.
Low, Heng Chin +2 more
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A Study on the Comparison of the Effectiveness of the Jackknife Method in the Biased Estimators [PDF]
, 2018 In this study, we proposed an alternative biased estimator. The linear regression model might lead to ill-conditioned design matrices because of the multicollinearity and thus result in inadequacy of the ordinary least squares estimator (OLS). Scientists
Yıldız, Nilgün
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Quantile regression in high-dimension with breaking [PDF]
, 2013 The paper considers a linear regression model in high-dimension for which the predictive variables can change the influence on the response variable at unknown times (called change-points).
Ciuperca, Gabriela
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Robust Liu-Type Estimator for SUR Model
Statistics, Optimization & Information Computing, 2021 The Liu-type estimator is one of the shrink estimators that is used to remedy for a problem of multicollinearityin SUR model, but it is sensitive to the outlier. In this paper, we introduce the S Liu-type (SLiu-type) and MM Liu-type estimator (MMLiu-type) for SUR model.
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On the Performance of Principal Component Liu-Type Estimator under the Mean Square Error Criterion
Journal of Applied Mathematics, 2013 Wu (2013) proposed an estimator, principal component Liu-type estimator, to overcome multicollinearity. This estimator is a general estimator which includes ordinary least squares estimator, principal component regression estimator, ridge estimator, Liu ...
Jibo Wu
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The beta Liu-type estimator: simulation and application
Hacettepe Journal of Mathematics and Statistics, 2023 The Beta Regression Model (BRM) is commonly used while analyzing data where the dependent variable is restricted to the interval $[0,1]$ for example proportion or probability. The Maximum Likelihood Estimator (MLE) is used to estimate the regression coefficients of BRMs.
Ali ERKOÇ +3 more
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Large Covariance Estimation by Thresholding Principal Orthogonal Complements [PDF]
, 2013 This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-
Fan, Jianqing +2 more
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Multivariate Location: Robust Estimators And Inference [PDF]
, 2004 The sample mean can have poor efficiency relative to various alternative estimators under arbitrarily small departures from normality. In the multivariate case, (affine equivariant) estimators have been proposed for dealing with this problem, but a ...
Keselman, H. J., Wilcox, Rand R.
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