Asymptotic Expansions of the Information Matrix Test Statistic
信息矩阵检验统计量的渐近展开
Conventional chi(superscript "2") approximations to the distribution of the information matrix test are shown to be inaccurate in models and with sample sizes commonly encountered. Interpreting a version of the information matrix test as an efficient score test leads to an alternative Edgeworth type approximation. This is calculated for the normal regression model and shown to be an improvement. Generally, the quality of the approximations is sensitive to the covariate…