Finite Sample Behavior of Tests for Grouped Heteroskedasticity
用蒙特卡洛方法比较了几种分组异方差检验在小样本下的表现，发现最简单、假设最少的检验方法效果不亚于更复杂的程序。
When the regression error variance is constant within subsets of data but differs across the subsets, grouped heteroskedasticity exists. Most tests for grouped heteroskedasticity are based on an asymptotic chi squared variable, and how well they perform in small samples is unknown. In this stud y, the performance of several of these, along with Breusch-Pagan tests, is examined using Monte Carlo methods. Generally, it is found that the tests that tend to be the easiest to apply and use the fewest assumptions are at least as good as somewhat more elaborate procedures. Copyright 1992 by MIT Press.