Results 21 to 30 of about 123,313 (259)
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Kurnaz, Fatma Sevinc, Akay, Kadri Ulas
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A New Biased Estimator Derived from Principal Component Regression Estimator [PDF]
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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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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A Study on the Comparison of the Effectiveness of the Jackknife Method in the Biased Estimators [PDF]
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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A new modified ridge-type estimator for the beta regression model: simulation and application
The beta regression model has become a popular tool for assessing the relationships among chemical characteristics. In the BRM, when the explanatory variables are highly correlated, then the maximum likelihood estimator (MLE) does not provide reliable ...
Muhammad Nauman Akram +3 more
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Robust Liu-Type Estimator for SUR Model
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
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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Quantile regression in high-dimension with breaking [PDF]
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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The beta Liu-type estimator: simulation and application
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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Multivariate Location: Robust Estimators And Inference [PDF]
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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