Cover Image

Prediction Suboptimality of the Lasso in Sparse Linear Regression

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Liu, Guo
Format:	Preprint
Published:	2026
Subjects:	Statistics Theory Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Provably Efficient Posterior Sampling for Sparse Linear Regression via Measure Decomposition
by: Montanari, Andrea, et al.
Published: (2024)

Finite-Sample Inference for Sparsely Permuted Linear Regression
by: Ota, Hirofumi, et al.
Published: (2026)

Lasso Penalization for High-Dimensional Beta Regression Models: Computation, Analysis, and Inference
by: Ramezani, Niloofar, et al.
Published: (2025)

Adaptive Lasso, Transfer Lasso, and Beyond: An Asymptotic Perspective
by: Takada, Masaaki, et al.
Published: (2023)

Design-based theory for Lasso adjustment in randomized block experiments and rerandomized experiments
by: Zhu, Ke, et al.
Published: (2021)

Detecting Parameter Instabilities in Functional Concurrent Linear Regression
by: Basu, Rupsa, et al.
Published: (2026)

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

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

Variable Selection and Minimax Prediction in High-dimensional Functional Linear Model
by: Guo, Xingche, et al.
Published: (2023)

Simulation-calibration testing for inference in Lasso regressions
by: Pluntz, Matthieu, et al.
Published: (2024)

Uniform Asymptotics and Confidence Regions Based on the Adaptive Lasso with Partially Consistent Tuning
by: Amann, Nicolai, et al.
Published: (2018)

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

Anytime-Valid Linear Models and Regression Adjusted Causal Inference in Randomized Experiments
by: Lindon, Michael, et al.
Published: (2022)

Rectified Linear Unit Regression
by: Oka, Tatsushi
Published: (2026)

Linear Regression Using Principal Components from General Hilbert-Space-Valued Covariates
by: Li, Xinyi, et al.
Published: (2025)

Functional Adaptive Double-Sparsity Estimator for Functional Linear Regression Model with Multiple Functional Covariates
by: Cao, Cheng, et al.
Published: (2023)

Model-free Bootstrap and Conformal Prediction in Regression: Conditionality, Conjecture Testing, and Pertinent Prediction Intervals
by: Wang, Yiren, et al.
Published: (2021)

Statistical Inference for High-Dimensional Robust Linear Regression Models via Recursive Online-Score Estimation
by: Zheng, Dian, et al.
Published: (2025)

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

Stability of a Generalized Debiased Lasso with Applications to Resampling-Based Variable Selection
by: Liu, Jingbo
Published: (2024)

Linear Regression from 1-bit Quantized Data
by: Hill, Daniel, et al.
Published: (2026)

On Robust Empirical Likelihood for Nonparametric Regression with Application to Regression Discontinuity Designs
by: Fang, Qin, et al.
Published: (2025)

Marked point processes intensity estimation using sparse group Lasso method applied to locations of lucrative and cooperative banks in mainland France
by: Artis, Amélie, et al.
Published: (2025)

Multiscale Quantile Regression with Local Error Control
by: Liu, Zhi, et al.
Published: (2024)

Estimating the Partially Linear Zero-Inflated Poisson Regression Model: a Robust Approach Using a EM-like Algorithm
by: Llop, María José, et al.
Published: (2026)

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

Statistically Significant Linear Regression Coefficients Solely Driven By Outliers In Finite-sample Inference
by: Reichel, Felix
Published: (2025)

Regression adjustment in covariate-adaptive randomized experiments with missing covariates
by: Fu, Wanjia, et al.
Published: (2025)

Estimation and Inference in Ultrahigh Dimensional Partially Linear Single-Index Models
by: Cui, Shijie, et al.
Published: (2024)

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

Bayesian Sphere-on-Sphere Regression with Optimal Transport Maps
by: Ng, Tin Lok James, et al.
Published: (2025)

Asymptotic Inference for Constrained Regression
by: Sankaranarayanan, Madhav, et al.
Published: (2025)

Distribution-in-distribution-out Regression
by: Chen, Xiaoyu, et al.
Published: (2024)

Doubly-Unlinked Regression for Dependent Data
by: Burman, Anik, et al.
Published: (2026)

Correcting the Coverage Bias of Quantile Regression
by: Gibbs, Isaac, et al.
Published: (2025)

Covariance Regression with High-Dimensional Predictors
by: He, Yuheng, et al.
Published: (2024)

Cellwise and Casewise Robust Multivariate Regression with Inference
by: Centofanti, Fabio, et al.
Published: (2026)

Quasi-maximum Likelihood Inference for Linear Double Autoregressive Models
by: Liu, Hua, et al.
Published: (2020)

Direct Bayesian Regression for Distribution-valued Covariates
by: Tang, Bohao, et al.
Published: (2023)