:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Di, Li, Xuanyu, Sun, Baoluo
Format:	Preprint
Published:	2025
Subjects:	Methodology
Online Access:	https://arxiv.org/abs/2504.18107
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Constructive Instrumental Variable Identification and Inference with Many Weak Interaction Moments
by: Zhang, Di, et al.
Published: (2025)

GENIUS-MAWII: For Robust Mendelian Randomization with Many Weak Invalid Instruments
by: Ye, Ting, et al.
Published: (2021)

On Doubly Robust Estimation with Nonignorable Missing Data Using Instrumental Variables
by: Sun, Baoluo, et al.
Published: (2023)

Testing High-Dimensional Mediation Effect with Arbitrary Exposure-Mediator Coefficients
by: Lin, Yinan, et al.
Published: (2023)

Quasi Instrumental Variable Methods for Stable Hidden Confounding and Binary Outcome
by: Liu, Zhonghua, et al.
Published: (2025)

Nonparametric Instrumental Variable Inference with Many Weak Instruments
by: van der Laan, Lars, et al.
Published: (2025)

A stableness of resistance model for nonresponse adjustment with callback data
by: Miao, Wang, et al.
Published: (2021)

Proximal Inference for Indirect and Intervening Effects in Population Interventions
by: Bai, Yang, et al.
Published: (2025)

Semiparametric Causal Inference for Right-Censored Outcomes with Many Weak Invalid Instruments
by: Bu, Qiushi, et al.
Published: (2025)

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

High-Dimensional Extreme Quantile Regression
by: Tang, Yiwei, et al.
Published: (2024)

High-Dimensional Expected Shortfall Regression
by: Zhang, Shushu, et al.
Published: (2023)

Complete Subset Averaging with Many Instruments
by: Lee, Seojeong, et al.
Published: (2018)

Proximal Path-Specific Inference
by: Bai, Yang, et al.
Published: (2026)

Fighting Noise with Noise: Causal Inference with Many Candidate Instruments
by: Zhang, Xinyi, et al.
Published: (2022)

Transfer Learning for High Dimensional Robust Regression
by: Yuan, Xiaohui, et al.
Published: (2024)

Cross-Semantic Transfer Learning for High-Dimensional Linear Regression
by: Jiang, Jiancheng, et al.
Published: (2025)

Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression
by: Wu, Anpeng, et al.
Published: (2024)

Learning the Covariance of Treatment Effects Across Many Weak Experiments
by: Bibaut, Aurélien, et al.
Published: (2024)

Statistical Inference on High Dimensional Gaussian Graphical Regression Models
by: Meng, Xuran, et al.
Published: (2024)

Model Form Identification in High-Dimensional Functional Linear Regressions
by: Guo, Xingche, et al.
Published: (2026)

Adaptive Test for High Dimensional Quantile Regression
by: Zhao, Ping, et al.
Published: (2025)

A Random-effects Approach to Regression Involving Many Categorical Predictors and Their Interactions
by: Sun, Hanmei, et al.
Published: (2024)

Demystifying Spectral Feature Learning for Instrumental Variable Regression
by: Meunier, Dimitri, et al.
Published: (2025)

Learning Treatment Representations for Downstream Instrumental Variable Regression
by: Lin, Shiangyi, et al.
Published: (2025)

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

Possibilistic Instrumental Variable Regression
by: Steiner, Gregor, et al.
Published: (2025)

Efficient Data Reduction Strategies for Big Data and High-Dimensional LASSO Regressions
by: Wang, Xin, et al.
Published: (2024)

TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression
by: He, Zelin, et al.
Published: (2024)

Evaluating Decision Rules Across Many Weak Experiments
by: Chou, Winston, et al.
Published: (2025)

Transfer Learning Under High-Dimensional Network Convolutional Regression Model
by: Wang, Liyuan, et al.
Published: (2025)

Exact Coordinate Descent for High-Dimensional Regularized Huber Regression
by: Kim, Younghoon, et al.
Published: (2025)

Adaptive Influence Diagnostics in High-Dimensional Regression
by: Soale, Abdul-Nasah, et al.
Published: (2025)

Regression Discontinuity Design with Potentially Many Covariates
by: Arai, Yoichi, et al.
Published: (2021)

Linear Regression with Weak Exogeneity
by: Mikusheva, Anna, et al.
Published: (2023)

Variational Bayesian Multiple Imputation in High-Dimensional Regression Models With Missing Responses
by: Li, Qiushuang, et al.
Published: (2025)

High Dimensional Factor Analysis with Weak Factors
by: Choi, Jungjun, et al.
Published: (2024)

Bayesian Transfer Learning for High-Dimensional Linear Regression via Adaptive Shrinkage
by: Jamshidian, Parsa, et al.
Published: (2025)

Envelope-Guided Regularization for Improved Prediction in High-Dimensional Multivariate Regression
by: Jacobson, Tate, et al.
Published: (2025)

Lecture Notes on High Dimensional Linear Regression
by: Quaini, Alberto
Published: (2024)