标题： 基于累积残差的模型诊断：R包gof 显示英文标题

标题： Model Diagnostics Based on Cumulative Residuals: The R-package gof

摘要： 广义线性模型在应用统计学的所有领域都得到了广泛应用，尽管在分布假设出现错误时仍可以得到正确的渐近推断，但获得可解释的结果需要一个正确指定的均值结构。 通常通过检查残差的各种散点图来检验预测变量的线性和函数形式，然而，判断这些图形的任务可能是具有挑战性的。 本文提出了一种基于残差聚合的广义线性模型以及结构方程模型诊断方法的实现，其中在零假设下渐近行为通过模拟来模仿。 还实现了一种用于检验Cox回归比例风险假设的程序。 显示英文摘要

摘要： The generalized linear model is widely used in all areas of applied statistics and while correct asymptotic inference can be achieved under misspecification of the distributional assumptions, a correctly specified mean structure is crucial to obtain interpretable results. Usually the linearity and functional form of predictors are checked by inspecting various scatter plots of the residuals, however, the subjective task of judging these can be challenging. In this paper we present an implementation of model diagnostics for the generalized linear model as well as structural equation models, based on aggregates of the residuals where the asymptotic behavior under the null is imitated by simulations. A procedure for checking the proportional hazard assumption in the Cox regression is also implemented.