Ando, T. and Li, K.C. (2017) A Weight-Relaxed Model Averaging Approach for High-Dimensional Generalized Linear Models. The Annals of Statistics, 45, 2654-2679.
https://doi.org/10.1214/17-AOS1538

has been cited by the following article:

• TITLE: A Review on High-Dimensional Frequentist Model Averaging

  AUTHORS: Peipei Fu, Juming Pan

  KEYWORDS: Model Averaging, High-Dimensional Regression Models, Stable Prediction

  JOURNAL NAME: Open Journal of Statistics, Vol.8 No.3, June 13, 2018

  ABSTRACT: Model averaging has attracted increasing attention in recent years for the analysis of high-dimensional data. By weighting several competing statistical models suitably, model averaging attempts to achieve stable and improved prediction. To obtain a better understanding of the available model averaging methods, their properties and the relationships between them, this paper is devoted to make a review on some recent progresses in high-dimensional model averaging from the frequentist perspective. Some future research topics are also discussed.