A review of the development and application of recursive residuals in linear models
A review of the development and application of recursive residuals in linear models
复制标题
线性模型中递归残差的发展和应用综述
DOI：
10.1080/01621459.1996.10476700
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发表时间：
1996
影响因子：
3.7
通讯作者：
W. Swallow
中科院分区：
文献类型：
--
作者：
F. Kianifard;W. Swallow
摘要递归残差在线性模型的各种应用中已被证明是有用的。与更熟悉的普通最小二乘残差或学生化残差不同，递归残差在模型下是独立的，也是同方差的。他们的独立性是特别有吸引力的用于开发测试统计。它们不是唯一定义的;它们的值取决于它们的计算顺序，尽管它们的属性并不如此。在某些应用中，人们可以利用这种阶数依赖性，再加上它们与计算它们的观测值明确一一对应的事实。在回归模型验证的几乎所有领域都建议使用递归残差。回归诊断已经从递归残差中构造出来，用于检测序列相关性、异方差性、功能误指定和结构变化。其他统计的基础上递归残差集中在检测离群…
Abstract Recursive residuals have been shown to be useful in a variety of applications in linear models. Unlike the more familiar ordinary least squares residuals or studentized residuals, recursive residuals are independent as well as homoscedastic under the model. Their independence is particularly appealing for use in developing test statistics. They are not uniquely defined; their values depend on the order in which they are calculated, although their properties do not. In some applications one can exploit this order dependence, coupled with the fact that they are in clear one-to-one correspondence with the observations for which they are calculated. Uses for recursive residuals have been suggested in almost all areas of regression model validation. Regression diagnostics have been constructed from recursive residuals for detecting serial correlation, heteroscedasticity, functional misspecification, and structural change. Other statistics based on recursive residuals have focused on detection of outli...