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Regression diagnostics methods for Liu estimator under the general linear regression model

机译:一般线性回归模型下Liu估计量的回归诊断方法

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This paper introduces the regression diagnostic methods for the Liu estimator under the general linear regression model with the autocorrelated error structure which is modeled by first-order autoregressive process. To identify the leverage observations, quasi-projection matrix is used, and to identify the influential observations DFFITS and Cook's D statistics which are single case deletion methods are used for the Liu estimator. For a special model with two explanatory variables, the leverage attitudes of the first observation are examined theoretically according to the autocorrelation coefficient and the Liu parameter. The proposed diagnostic methods are investigated through a numerical example.
机译:本文介绍了在具有一阶自回归过程建模的自相关误差结构的一般线性回归模型下,Liu估计量的回归诊断方法。为了确定杠杆观察,使用了准投影矩阵,并确定了影响估计值DFFITS和Cook的D统计量,这是Liu估计量的单例删除方法。对于具有两个解释变量的特殊模型,理论上根据自相关系数和Liu参数检查了第一次观察的杠杆态度。通过数值示例研究了提出的诊断方法。

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