By employing the concept of statistical curvatures, the information loss of the maximum likelihood estimator and the generalized least squares estimator is investigated.
利用统计曲率的概念,研究结构方程模型的最大似然估计量和广义最小二乘估计量的信息损失,得到了简明的结果。
This paper studies linear regression models with dependent errors, and we introduce the jackknifed least squares estimator and generalized jackknife least squares estimator.
在误差为相依的情况下,讨论了线性回归模型的刀切最小二乘估计与广义刀切最小二乘估计。
This paper studies linear regression models with dependent errors, and we introduce the jackknifed least squares estimator and generalized jackknife least squares estimator.
在误差为相依的情况下,讨论了线性回归模型的刀切最小二乘估计与广义刀切最小二乘估计。
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