Liu Estimator
Modifying Two-Parameter Ridge Liu Estimator Based on Ridge Estimation
... π½Μ πΏπ
πΈ (π, d) = (πΛπ + I) β1 (πΛπ + ππ½Μ π
πΈ (k)) (6) by augmenting the equation (βd/π 1/2 )π½Μ π
πΈ (π) = k 1/2 Ξ² + Ξ΅ to the model in (1) and then using the ordinary least squares method . This estimator has superior ...
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A New Stochastic Restricted Liu Estimator for the Logistic Regression Model
... Restricted Liu Estimator in logistic regression ...Estimation, Liu Estimator Stochastic Restricted Maxi- mum Likelihood Estimator ...
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More on the Preliminary Test Stochastic Restricted Liu Estimator in Linear Regression Model
... suitable estimator, and it can also be used as another estimator with combining properties of both ...Test Estimator (OSPE) was proposed by Wijekoon ...Restricted Liu Estimator (PTSRLE) ...
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Identifying Unusual Observations in Ridge Regression Linear Model Using Box Cox Power Transformation Technique
... The second data set is [13] to explain the influential observations on the Liu estimator. The scaled condition number of this data set is 43,275 (see [14]). This large value suggests the presence severe ...
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Comparison of Some Suggested Estimators Based on Differencing Technique in the Partial Linear Model Using Simulation
... difference-based estimator ο’ Λ diff by using MSE ...ridge estimator and Liu type estimator for the partially linear semiparametric model were studied when the errors are independent with equal ...
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Stochastic Restricted Maximum Likelihood Estimator in Logistic Regression Model
... Logistic Estimator (PCLE) by Aguilera et ...Regression Estimator (MLRE) by Nja et al. (2013) [6], Liu Estimator by Mansson et ...and Liu-type estimator by Inan and Erdogan (2013) ...
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TWO STAGE LIU REGRESSION ESTIMATOR
... new estimator for multicollinearity and autocorrelated ...Stages Liu estimator (TL) for the multiple linear regression model which suffers from autocorrelation AR(1) and multicollinearity ...proposed ...
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Performance of Existing Biased Estimators and the Respective Predictors in a Misspecified Linear Regression Model
... class estimator and r-k class estimator over some existing esti- mators, ...Regression Estimator (MRE) under misspecified regres- sion model due to excluding relevant variable with correctly ...
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Estimator selection
... The theory of estimation with tests has been considered a powerful theoretical tool for a long time. Actually, it does not require many assumptions on the observations and very general optimal risk bounds can be shown ...
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Estimating a Bounded Normal Mean Under the LINEX Loss Function
... It is worth mentioning that the problem of estimating a normal mean ο± in the case where ο± is bounded below, i.e., ο± ο³ a , for some constant , a also received considerable attention in the literature. Estimation of a ...
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Empirical likelihood based inference in Poisson autoregressive model with conditional moment restrictions
... The EL as an alternative to the bootstrap for constructing conο¬dence regions was intro- duced by Owen [οο, οοΊ]. The method deο¬nes an EL ratio function to construct conο¬dence regions. Important features of the empirical ...
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On comparison some estimators in small area study
... synthetic estimator using the previous year batting average, two composite estimators that we mentioned, the Bayes estimators using either noninformative or informative prior ...
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4. Sijia Zhu and Gang Liu
... SOD, POD and CAT are important enzymes that protect cells against reactive oxygen species damage (Frank et al., 2001; Dong et al., 2013; Ma and Wang, 2013). SOD is an active substance derived from the living body, which ...
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LIU/JINNLIANGMR0162465502405 15A FLIGHT INFORMATION
... IMPORTANT CONSUMER NOTICES Notice of Baggage Liability Limitations Β For domestic travel between points within the United States except for domestic portions of international journeys, U[r] ...
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Bob Eisenberg Jinn Liang Liu
... Scharfetter and Gummel, IEEE Trans. Elec. Dev.16, 64 (1969) P. Markowich, et al, IEEE Trans. Elec. Dev. 30, 1165 (1983). Zheng, Chen, and G.-W. Wei, J. Comp. Phys. 230, 5239 (2011). Geng, S. Yu, and G.-W. Wei, J. Chem. ...
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Estimators of Linear Regression Model and Prediction under Some Assumptions Violation
... diction of its values often becomes very essential and necessary. Moreover, the linear regression model is for- mulated under some basic assumptions. Among these as- sumptions are regressors being assumed to be non-sto- ...
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ESTIMATORS OF LINEAR REGRESSION MODEL WITH AUTOCORRELATED ERRROR TERMS AND PREDICTION USING CORRELATED UNIFORM REGRESSORS
... These figures reveal that the performances of COR and ML estimators at each level of multicollinearity over the levels of autocorrelation are convex β like while that of the OLS and PC estimators are concave. Also, as ...
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On estimating a slope and intercept in a nonparametric statistics course
... pairwise averages of residuals based on Theil's estimator provides.. an attractive estimator of the intercept.[r] ...
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International Journal of Data Envelopment Analysis and *Operations Research*
... the best one for small moderate whereas the maximum likelihood estimator is the best to estimate the parameter for moderate and large samples. Other empirical experiments are conducted to build a model for ...
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Adjustment of the Auxiliary Variable(s) for Estimation of a Finite Population Mean
... In this section we shall see whether the proposed estimator with transformation y tran f ( ) performs better than the proposed estimator without transformation y prop . In Table 6, we present the numerical ...
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