Cover Image

Optimal Bias-Correction and Valid Inference in High-Dimensional Ridge Regression: A Closed-Form Solution

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gao, Zhaoxing, Tsay, Ruey S.
Format:	Preprint
Published:	2024
Subjects:	Econometrics Methodology Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Forward Regression via Gram-Schmidt Orthogonalization for Ultra-High Dimensional Linear Models
by: Chen, Jialuo, et al.
Published: (2025)

Supervised Dynamic PCA: Linear Dynamic Forecasting with Many Predictors
by: Gao, Zhaoxing, et al.
Published: (2023)

Modeling High-Dimensional Dependent Data in the Presence of Many Explanatory Variables and Weak Signals
by: Gao, Zhaoxing, et al.
Published: (2024)

Sparse Asymptotic PCA: Identifying Sparse Latent Factors Across Time Horizon in High-Dimensional Time Series
by: Gao, Zhaoxing
Published: (2024)

LASSO Inference for High Dimensional Predictive Regressions
by: Gao, Zhan, et al.
Published: (2024)

Vector AutoRegressive Moving Average Models: A Review
by: Düker, Marie-Christine, et al.
Published: (2024)

Quantile Vector Autoregression without Crossing
by: Ando, Tomohiro, et al.
Published: (2026)

High-Dimensional Spatial Arbitrage Pricing Theory with Heterogeneous Interactions
by: Gao, Zhaoxing, et al.
Published: (2025)

Structural Change Detection in High-Dimensional Transformed Factor Models via Canonical Correlation Analysis
by: Jia, Lei, et al.
Published: (2026)

Denoising and Multilinear Projected-Estimation of High-Dimensional Matrix-Variate Factor Time Series
by: Gao, Zhaoxing, et al.
Published: (2023)

Ridge Estimation of High Dimensional Two-Way Fixed Effect Regression
by: He, Junnan, et al.
Published: (2026)

Cross-Validated Causal Inference: a Modern Method to Combine Experimental and Observational Data
by: Yang, Xuelin, et al.
Published: (2025)

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

Debiased Ill-Posed Regression
by: Ghassami, AmirEmad, et al.
Published: (2025)

Debiased Nonparametric Regression for Statistical Inference and Distributionally Robustness
by: Kato, Masahiro
Published: (2024)

Machine-Learning-Assisted Comparison of Regression Functions
by: Yan, Jian, et al.
Published: (2025)

Linear Multidimensional Regression with Interactive Fixed-Effects
by: Freeman, Hugo
Published: (2022)

Shrinkage-Based Regressions with Many Related Treatments
by: Dilber, Enes, et al.
Published: (2025)

Detecting and Mitigating Group Bias in Heterogeneous Treatment Effects
by: Persson, Joel, et al.
Published: (2026)

Optimal Conditional Inference in Adaptive Experiments
by: Chen, Jiafeng, et al.
Published: (2023)

Adaptive Principal Component Regression with Applications to Panel Data
by: Agarwal, Anish, et al.
Published: (2023)

Direct Bias-Correction Term Estimation for Average Treatment Effect Estimation
by: Kato, Masahiro
Published: (2025)

A Causal Inference Framework for Data Rich Environments
by: Abadie, Alberto, et al.
Published: (2025)

Regularizing Extrapolation in Causal Inference
by: Arbour, David, et al.
Published: (2025)

Inference for Batched Adaptive Experiments
by: Kemper, Jan, et al.
Published: (2025)

Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions
by: Agarwal, Abhineet, et al.
Published: (2023)

Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameters
by: Dalal, Abhinandan, et al.
Published: (2024)

Applied Causal Inference Powered by ML and AI
by: Chernozhukov, Victor, et al.
Published: (2024)

Improved Inference for CSDID Using the Cluster Jackknife
by: Karim, Sunny R., et al.
Published: (2026)

A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference
by: Parikh, Harsh, et al.
Published: (2025)

A Unified Theory for Causal Inference: Direct Debiased Machine Learning via Bregman-Riesz Regression
by: Kato, Masahiro
Published: (2025)

Can We Validate Counterfactual Estimations in the Presence of General Network Interference?
by: Shirani, Sadegh, et al.
Published: (2025)

Effect Identification and Unit Categorization in the Multi-Score Regression Discontinuity Design with Application to LED Manufacturing
by: Schwarz, Philipp Alexander, et al.
Published: (2025)

Doubly Robust Inference in Causal Latent Factor Models
by: Abadie, Alberto, et al.
Published: (2024)

Estimation and Inference for Causal Functions with Multiway Clustered Data
by: Liu, Nan, et al.
Published: (2024)

Double Robust Bayesian Inference on Average Treatment Effects
by: Breunig, Christoph, et al.
Published: (2022)

Entrywise Inference for Missing Panel Data: A Simple and Instance-Optimal Approach
by: Yan, Yuling, et al.
Published: (2024)

Vector Copula Variational Inference and Dependent Block Posterior Approximations
by: Fu, Yu, et al.
Published: (2025)

Double Machine Learning meets Panel Data -- Promises, Pitfalls, and Potential Solutions
by: Fuhr, Jonathan, et al.
Published: (2024)

Triple/Debiased Lasso for Statistical Inference of Conditional Average Treatment Effects
by: Kato, Masahiro
Published: (2024)