Cover Image

Nodewise Loreg: Nodewise $L_0$-penalized Regression for High-dimensional Sparse Precision Matrix Estimation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Shu, Hai, Chen, Ziqi, Zhang, Yingjie, Zhu, Hongtu
Format:	Preprint
Published:	2024
Subjects:	Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Variable Clustering via Distributionally Robust Nodewise Regression
by: Wang, Kaizheng, et al.
Published: (2022)

On Ridge Estimation in High-dimensional Rotationally Sparse Linear Regression
by: Liang, Libin, et al.
Published: (2024)

Bayesian High-dimensional Linear Regression with Sparse Projection-posterior
by: Pal, Samhita, et al.
Published: (2024)

Iterative Collaborative Filtering for Sparse Matrix Estimation
by: Borgs, Christian, et al.
Published: (2017)

Direct Estimation of Eigenvalues of Large Dimensional Precision Matrix
by: Zhou, Jie, et al.
Published: (2025)

A Modern Theory for High-dimensional Cox Regression Models
by: Ye, Hanxuan, et al.
Published: (2022)

Transfer Learning for High-dimensional Quantile Regression with Distribution Shift
by: Bai, Ruiqi, et al.
Published: (2024)

CARE: Large Precision Matrix Estimation for Compositional Data
by: Zhang, Shucong, et al.
Published: (2023)

High-dimensional (Group) Adversarial Training in Linear Regression
by: Xie, Yiling, et al.
Published: (2024)

A Two-Step Projection-Based Goodness-of-Fit Test for Ultra-High Dimensional Sparse Regressions
by: Tan, Falong, et al.
Published: (2024)

Online Sparse Regression with Expanding Observables
by: Yang, Ying, et al.
Published: (2026)

Causal Inference in Biomedical Imaging via Functional Linear Structural Equation Models
by: Li, Ting, et al.
Published: (2026)

Sparse Data-Driven Random Projection in Regression for High-Dimensional Data
by: Parzer, Roman, et al.
Published: (2023)

Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
by: Jin, Yanhao, et al.
Published: (2024)

Spatially Randomized Designs Can Enhance Policy Evaluation
by: Yang, Ying, et al.
Published: (2024)

Non-Asymptotic Analysis of Data Augmentation for Precision Matrix Estimation
by: Morisset, Lucas, et al.
Published: (2025)

Finite- and Large- Sample Inference for Model and Coefficients in High-dimensional Linear Regression with Repro Samples
by: Wang, Peng, et al.
Published: (2022)

Sparse Max-Affine Regression
by: Kanj, Haitham, et al.
Published: (2024)

Debiased Prediction Inference with Non-sparse Loadings in Misspecified High-dimensional Regression Models
by: Liang, Libin, et al.
Published: (2025)

Optimal Sparse Singular Value Decomposition for High-dimensional High-order Data
by: Zhang, Anru, et al.
Published: (2018)

Statistical Inference in High-dimensional Poisson Regression with Applications to Mediation Analysis
by: Rakshit, Prabrisha, et al.
Published: (2024)

Minimax Optimal Probability Matrix Estimation For Graphon With Spectral Decay
by: Chen, Yuchen, et al.
Published: (2024)

Prediction Suboptimality of the Lasso in Sparse Linear Regression
by: Liu, Guo
Published: (2026)

Estimation of High-dimensional Nonlinear Vector Autoregressive Models
by: Han, Yuefeng, et al.
Published: (2025)

Adaptive Long-Run Variance Thresholding for Sparse Covariance Estimation in High-Dimensional Time Series
by: Zhang, Wenhao, et al.
Published: (2026)

Uniform Estimation and Inference for Nonparametric Partitioning-Based M-Estimators
by: Cattaneo, Matias D., et al.
Published: (2024)

Debiased Bayesian Inference for High-dimensional Regression Models
by: Chen, Qihui, et al.
Published: (2025)

An Easily Tunable Approach to Robust and Sparse High-Dimensional Linear Regression
by: Sasai, Takeyuki, et al.
Published: (2025)

Double-Estimation-Friendly Inference for High-Dimensional Measurement Error Models with Non-Sparse Adaptability
by: Cui, Shijie, et al.
Published: (2024)

Debiased Inference for High-Dimensional Regression Models Based on Profile M-Estimation
by: Wang, Yi, et al.
Published: (2025)

High-dimensional Covariance Estimation by Pairwise Likelihood Truncation
by: Casa, Alessandro, et al.
Published: (2024)

High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models
by: Liang, Tengyuan, et al.
Published: (2022)

A Unified Approach to Statistical Estimation Under Nonlinear Observations: Tensor Estimation and Matrix Factorization
by: Chen, Junren, et al.
Published: (2025)

Precision and Cholesky Factor Estimation for Gaussian Processes
by: Chen, Jiaheng, et al.
Published: (2024)

Empirical Bayes When Estimation Precision Predicts Parameters
by: Chen, Jiafeng
Published: (2022)

Support Recovery and $\ell_2$-Error Bound for Sparse Regression with Quadratic Measurements via Weakly-Convex-Concave Regularization
by: Fan, Jun, et al.
Published: (2026)

Factor Strength Estimation in Vector and Matrix Time Series Factor Models
by: Chen, Weilin, et al.
Published: (2024)

Sub-Gaussian High-Dimensional Covariance Matrix Estimation under Elliptical Factor Model with 2 + εth Moment
by: Ding, Yi, et al.
Published: (2024)

A Sparse Beta Regression Model for Network Analysis
by: Stein, Stefan, et al.
Published: (2020)

Generalized Principal Component Analysis for Large-dimensional Matrix Factor Model
by: He, Yong, et al.
Published: (2024)