Foundations for Envelope Models and Methods
Foundations for Envelope Models and Methods
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DOI：
10.1080/01621459.2014.983235
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发表时间：
2015-06-01
影响因子：
3.7
通讯作者：
Zhang, Xin
中科院分区：
文献类型：
--
作者：
Cook, R. Dennis;Zhang, Xin
包络是最近由Cook、Li和Chiaromonte提出的一种减少多元线性回归中估计和预测变异的方法。我们扩展了他们的配方，提出了一个一般的定义的信封和一个一般的框架，适应信封的方法，任何估计过程。我们将新的包络方法应用于加权最小二乘、广义线性模型和考克斯回归。模拟和说明性的数据分析表明，包络方法显着提高标准方法在线性判别分析，逻辑回归和泊松回归的潜力。本文的补充材料可在网上查阅。
Envelopes were recently proposed by Cook, Li and Chiaromonte as a method for reducing estimative and predictive variations in multivariate linear regression. We extend their formulation, proposing a general definition of an envelope and a general framework for adapting envelope methods to any estimation procedure. We apply the new envelope methods to weighted least squares, generalized linear models and Cox regression. Simulations and illustrative data analysis show the potential for envelope methods to significantly improve standard methods in linear discriminant analysis, logistic regression and Poisson regression. Supplementary materials for this article are available online.