Optimal estimation of direction in regression models with large number of parameters
作者：
Highlights：
• Regression models with a large number of parameters are considered.
• Simple estimators to optimally estimate the direction in regression models are studied, and considered through analytic and new examples.
• Comparison of the simple estimators with the ‘state-of-the-art’ is considered.
摘要
•Regression models with a large number of parameters are considered.•Simple estimators to optimally estimate the direction in regression models are studied, and considered through analytic and new examples.•Comparison of the simple estimators with the ‘state-of-the-art’ is considered.
论文关键词：Random balance,Screening experiments,Box–Wilson methodology,LASSO,Ridge regression
论文评审过程：Received 15 February 2017, Revised 2 May 2017, Accepted 14 May 2017, Available online 31 May 2017, Version of Record 18 October 2017.
论文官网地址：https://doi.org/10.1016/j.amc.2017.05.050
