Misspecification Testing: A Comprehensive Approach
指出针对回归模型单个假设的误设定检验常导致错误结论，通过蒙特卡洛实验证明综合使用个体与联合检验可降低这种风险，并提出实用检验策略。
Abstract Misspecification tests of individual assumptions underlying regression models often lead to erroneous conclusions regarding source of misspecification. Monte Carlo experiments demonstrate that a comprehensive set of individual and joint tests reduces the likelihood of such conclusions. A practical testing strategy is proposed and suggestions made regarding its implementation.