蒙特卡罗方法下线性模型的异方差性检验方法

Heteroscedasticity Testing Method by Linear Model Under the Monte Carlo Method

在已有的异方差性检验方法的基础上,运用蒙特卡罗方法,借助permutation检验思想,在不假定随机扰动项服从同一分布族的条件下,通过从大样本中提取大量的子样本,不断对线性模型进行拟合和检验,根据异方差为真的频率大小,给出了一种新的异方差检验方法。随机模拟表明本检验方法优于传统方法。

Existing Heteroscedasticity testing method is presented in this paper,on the basis of using the Monte Carlo method,with the help of a thought of permutation test,without assuming that submitting to the identically distribution family of the random disturbed term,through a large amount of extracted from large sample sample,constantly to fit linear models and inspection,according to Heteroscedasticity for really frequency size,put forward a new Heteroscedasticity testing method is given.Stochastic simulation shows that the test method is better than traditional methods.