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。
By employing the concept of statistical curvatures, the information loss of the maximum likelihood estimator and the generalized least squares estimator is investigated.
本文利用最小二乘估计给出噪声为ARMA序列线性模型中时变参数估计，并讨论了估计量的相容性问题。
In this paper we get the estimation of time-varying parameters in linear regression model with ARMA noise by the least square method and discuss the consistency of the estimation at the same time.
在半参数回归模型中采用最小二乘估计方法结合局部多项式方法来估计未知量，在一定条件下得到了估计量的相合性。
And estimated the unknown quantity using the methods of least square estimation and local polynomial estimation, obtained the consistency of estimation under certain condition.
在半参数回归模型中采用最小二乘估计方法结合局部多项式方法来估计未知量，在一定条件下得到了估计量的相合性。
And estimated the unknown quantity using the methods of least square estimation and local polynomial estimation, obtained the consistency of estimation under certain condition.
应用推荐