Bootstrap Approximations in Model Checks for Regression
本文研究用野Bootstrap方法近似回归模型检验中残差标记的经验过程分布，并通过模拟和实际数据验证方法有效性。
Abstract Let M = mθθ θ be a parametric model for an unknown regression function m. For example, M may consist of all polynomials or trigonometric polynomials with a given bound on the degree. To check the full model M (i.e., to test for H 0: m ε M), it is known that optimal tests should be based on the empirical process of the regressors marked by the residuals. In this article we show that the distribution of this process may be approximated by the wild bootstrap. The method is applied to simulated datasets as well as to real data.