A Model-Averaging Approach for High-Dimensional Regression

By Tomohiro Ando, Ker-Chau Li. 2014

215 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/068a00f851e6bcc5812c4f0c317e3ad1caf732a2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

1. Guohua Zou
2. Xinyu Zhang
3. Hua Liang
4. Yan Gao
5. Shouyang Wang
6. Dalei Yu
7. Tomohiro Ando
8. Ker-Chau Li

Citations in the corpus

• On sparse ensemble methods: An application to short-term predictions of the evolution of COVID-19 (2021, background): “Hence, it may be more convenient to build an ensemble where some accuracy measure, such as a (cross-validation) estimate of the expected squared error or of the absolute error ( Ando & Li, 2014; Bates & Granger, 1969 ), is optimized at each forecast origin.”
• Model averaging based on leave-subject-out cross-validation (2016, background): “Condition 9 requires that ξ ∗ T increases to infinity at a rate quicker than √ T → ∞, which is implied by the condition (7) of Ando and Li (2014) and our Condition 3.”
• A weight-relaxed model averaging approach for high-dimensional generalized linear models (2017, methodology): “For example, the method of bounding the term |L̃(w) − L(w)|, a critical step in the proof of (12) in Ando and Li (2014), is not applicable here.”
• Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series (2018, methodology): “To address this issue, Ando and Li (2014) proposed a two-step model averaging method for a high-dimensional linear regression with the dimension of the covariates larger than the sample size and show that such a method works well both theoretically and numerically.”
• Optimal Model Averaging Estimation for Generalized Linear Models and Generalized Linear Mixed-Effects Models (2016, background): “Condition C.3 requires that ξn grows at a rate no slower than n1/2, is the same as the third part of Condition (A7) of Zhang, Zou, and Liang (2014) and is also implied by Conditions (7) and (8) of Ando and Li (2014).”