渐进正态分布就是大样本的统计量的性质,也就是说你的最小二乘法得到的参数估计的渐进正态分布,因此没有你所谓的同方差性

一般序列模型都是建立正态分布,但是他们残差可能相关,最佳例子是ARCH & GARCH

还是不是很明白，渐进正态，应该就是说的大样本下乘正态分布的吧，正态分布不就一个方差吗，N（0，V），为什么说不是同方差，下面是我从维基上搜到的，关于渐进正态，大大再帮忙看看。

非常感谢

An asymptotically normal estimator is a consistent estimator whose distribution around the true parameter θ approaches a normal distribution with standard deviation shrinking in proportion to as the sample size n grows. Using to denote convergence in distribution, t_n is asymptotically normal if

for some V, which is called the asymptotic variance of the estimator.

The central limit theorem implies asymptotic normality of the sample mean as an estimator of the true mean. More generally, maximum likelihood estimators are asymptotically normal under fairly weak regularity conditions — see the asymptotics section of the maximum likelihood article.