Chow-type Tests Under Heteroscedasticity
针对多个回归中共同结构参数的推断问题，提出在残差方差不等且未知情况下的综合解决方案，利用广义p值方法，并以股票纳入标普500指数对收益率的影响为例说明。
Inference for structural parameters that are common to several regressions is a frequent problem of statistical practice. In the unlikely case that the residual error variances are equal for all regressions, the inference problem usually has a closed–form solution within the standard regression framework. In the case of unequal and unknown residual error variances, the problem falls into the category of Behrens-Fisher problems. This article describes a comprehensive solution to this inference problem using the concept of a generalized p value introduced by Tsui and Weerahandi in 1989. An example investigating the effect on stock return due to a firm's inclusion in the Standard and Poor's 500 illustrates the method.