随机误差项

文中对计量经济模型中的随机误差项u谈了三点认识：如何理解随机误差项u的不可观测性；

This paper gives three points of view about the stochastic error ( u ) in econometric models .

另一方面，最小二乘估计中随机误差项的假设过于严格。

On the other hand , the assumption of random error term is too stringent .

然而，在大多数情况下我们假设随机误差项是独立同分布的。但是这种假设情形不一定总是合理的。

However , the assumption of independent and identical distributed errors in general metamodel is not always true .

线性模型的基本特征是，模型的未知参数是线性的，同时又线性的包含了随机误差项。

The basic characteristic of the linear model is the unknown parameter of the model is linear and it also includes the linear random error .

针对由Koyck变换而引出的两个新问题：随机误差项的自相关，以及随机误差项与解释变量之间的相关，进行了深入的讨论和研究。

According to the autocorrelations of residual error and the correlations between residual error and explanatory variable to the models estimation , these estimation questions were deeply discussed .

文章将在同一时点影响样本个体的共同因素从随机误差项分离出来，建立了相应的二元响应面板数据模型。

Secondly , writer separated out common factors of individual at the same point from a random error term , and established a corresponding binary response panel data model .

如何从数学和经济学两个方面去理解用序列残差的方差去估计随机误差项的方差。

How to recognize the difference between the variances of series error and stochastic error and how to comprehend estimation of the variance of stochastic error by using the variance of series error .

用转位对消常值漂移，并忽略惯性器件随机漂移误差项。

The basic method is to eliminate the constant drift by position transformation , ignore the random drift of inertial unit .

针对随机前沿面模型中随机误差项分解的困难，本文采用最大似然估计法建立了求解模型，实证中很好的解决了随机前沿面模型中误差项的分解。

For the difficulty of the error decomposing of the stochastic frontier model , maximum likelihood estimation is adopted to construct the solving model , and the error decomposing is solved satisfactorily in the empirical research .