Improved two-stage model averaging for high-dimensional linear regression, with application to Riboflavin data analysis

Improved two-stage model averaging for high-dimensional linear regression, with application to Riboflavin data analysis

Background: 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. In this paper, we develop a two-stage model averag...

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Bibliographic Details
Main Author: Pan, J. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
Accurate prediction
Clustering algorithms
computer simulation
Computer Simulation
Corresponding weights
Cross-validation
data analysis
Data Analysis
Forecasting
High dimensional data
High-dimensional models
High-dimensional regression
High-dimensional regressions
Jackknife
Linear Models
Model averaging
Models, Statistical
Predictive performance
Quadratic programming
Regression analysis
riboflavin
Riboflavin
Squared prediction errors
statistical model
Variable selection
Variable selection methods
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