Improved estimators for semi-supervised high-dimensional regression model
From MaRDI portal
Publication:2106769
DOI10.1214/22-EJS2070MaRDI QIDQ2106769
David Azriel, Yair Goldberg, Ilan Livne
Publication date: 19 December 2022
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2102.07203
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Consistent variable selection for functional regression models
- Some aspects of minimum variance unbiased estimation in presence of ancillary statistics
- Heritability estimation in high dimensional sparse linear mixed models
- Unbiased estimation for some non-parametric families of distributions
- Some incomplete and boundedly complete families of distributions
- Adaptive estimation of high-dimensional signal-to-noise ratios
- A fast and consistent variable selection method for high-dimensional multivariate linear regression with a large number of explanatory variables
- Variance estimation in high-dimensional linear models
- Scaled sparse linear regression
- A Perspective on the Use of Control Variables to Increase the Efficiency of Monte Carlo Simulations
- Asymptotic Statistics
- Variance Estimation Using Refitted Cross-Validation in Ultrahigh Dimensional Regression
- Post‐selection inference for ‐penalized likelihood models
- Panning for Gold: ‘Model-X’ Knockoffs for High Dimensional Controlled Variable Selection
- Semisupervised Inference for Explained Variance in High Dimensional Linear Regression and its Applications
- Optimal Estimation of Genetic Relatedness in High-Dimensional Linear Models
- EigenPrism: Inference for High Dimensional Signal-to-Noise Ratios
This page was built for publication: Improved estimators for semi-supervised high-dimensional regression model