The envelope model was first introduced as a parsimonious version of multivariate linear regression. It uses dimension reduction techniques to remove immaterial variation in the data and has the potential to gain efficiency in estimation and improve prediction. Many advances have taken place since its introduction, and the envelope model has been applied to many contexts in multivariate analysis, including partial least squares, generalised linear models, Bayesian analysis, variable selection and quantile regression, among others. This article serves as a review of the envelope model and its developments for those who are new to the area.

中文翻译：

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信封模型综述

包络模型最初是作为多元线性回归的简化版本引入的。它使用降维技术来消除数据中的无关紧要的变化，并有可能提高估计效率并改善预测。自引入以来已取得了许多进步，并且包络模型已应用于多元分析中的许多上下文，包括偏最小二乘，广义线性模型，贝叶斯分析，变量选择和分位数回归等。本文是对信封模型及其对那些新来的人的发展的回顾。