Image de couverture de livre

Cross-Fitting-Free Debiased Machine Learning with Multiway Dependence

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Chen, Kaicheng, Chiang, Harold D.
Format:	Preprint
Publié:	2026
Sujets:	Econometrics Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Multiway empirical likelihood
par: Chiang, Harold D, et autres
Publié: (2021)

An Introduction to Double/Debiased Machine Learning
par: Ahrens, Achim, et autres
Publié: (2025)

A Unified Framework for Debiased Machine Learning: Riesz Representer Fitting under Bregman Divergence
par: Kato, Masahiro
Publié: (2026)

Estimation and Inference for Causal Functions with Multiway Clustered Data
par: Liu, Nan, et autres
Publié: (2024)

Difference-in-Differences with Time-varying Continuous Treatments using Double/Debiased Machine Learning
par: Haddad, Michel F. C., et autres
Publié: (2024)

Double/Debiased Machine Learning for Treatment and Causal Parameters
par: Chernozhukov, Victor, et autres
Publié: (2016)

Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibration
par: Ballinari, Daniele, et autres
Publié: (2024)

Empirical Likelihood for Random Forests and Ensembles
par: Chiang, Harold D., et autres
Publié: (2025)

Direct Debiased Machine Learning via Bregman Divergence Minimization
par: Kato, Masahiro
Publié: (2025)

Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameters
par: Dalal, Abhinandan, et autres
Publié: (2024)

Debiased Ill-Posed Regression
par: Ghassami, AmirEmad, et autres
Publié: (2025)

genriesz: A Python Package for Automatic Debiased Machine Learning with Generalized Riesz Regression
par: Kato, Masahiro
Publié: (2026)

ScoreMatchingRiesz: Score Matching for Debiased Machine Learning and Policy Path Estimation
par: Kato, Masahiro
Publié: (2025)

Covariate Balancing and Riesz Regression Should Be Guided by the Neyman Orthogonal Score in Debiased Machine Learning
par: Kato, Masahiro
Publié: (2026)

Identification and Debiased Learning of Causal Effects with General Instrumental Variables
par: Chen, Shuyuan, et autres
Publié: (2025)

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

Inference in High-Dimensional Panel Models: Two-Way Dependence and Unobserved Heterogeneity
par: Chen, Kaicheng
Publié: (2025)

Double Debiased Covariate Shift Adaptation Robust to Density-Ratio Estimation
par: Kato, Masahiro, et autres
Publié: (2023)

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

Macroeconomic Forecasting and Machine Learning
par: Chi, Ta-Chung, et autres
Publié: (2025)

Dual Interpretation of Machine Learning Forecasts
par: Coulombe, Philippe Goulet, et autres
Publié: (2024)

Model Averaging and Double Machine Learning
par: Ahrens, Achim, et autres
Publié: (2024)

Causal Machine Learning for Moderation Effects
par: Bearth, Nora, et autres
Publié: (2024)

Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning
par: Rombouts, Jeroen, et autres
Publié: (2024)

The Uncertainty of Machine Learning Predictions in Asset Pricing
par: Liao, Yuan, et autres
Publié: (2025)

Inference for Regression with Variables Generated by AI or Machine Learning
par: Battaglia, Laura, et autres
Publié: (2024)

Unemployment Dynamics Forecasting with Machine Learning Regression Models
par: Kim, Kyungsu
Publié: (2025)

Machine-Learning-Assisted Comparison of Regression Functions
par: Yan, Jian, et autres
Publié: (2025)

Neighborhood Stability in Double/Debiased Machine Learning with Dependent Data
par: Cao, Jianfei, et autres
Publié: (2025)

Enhancing Poverty Targeting with Spatial Machine Learning: An application to Indonesia
par: Martinez, Rolando Gonzales, et autres
Publié: (2025)

Double Machine Learning for Static Panel Models with Fixed Effects
par: Clarke, Paul S., et autres
Publié: (2023)

Double Machine Learning for Causal Inference under Shared-State Interference
par: Hays, Chris, et autres
Publié: (2025)

Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study
par: Bach, Philipp, et autres
Publié: (2024)

A Granular Framework for Construction Material Price Forecasting: Econometric and Machine-Learning Approaches
par: Lyu, Boge, et autres
Publié: (2025)

Debiased Bayesian Inference for High-dimensional Regression Models
par: Chen, Qihui, et autres
Publié: (2025)

Navigating Inflation in Ghana: How Can Machine Learning Enhance Economic Stability and Growth Strategies
par: Baidoo, Theophilus G., et autres
Publié: (2024)

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

Can Moran Eigenvectors Improve Machine Learning of Spatial Data? Insights from Synthetic Data Validation
par: Li, Ziqi, et autres
Publié: (2025)

Debiased Regression for Root-N-Consistent Conditional Mean Estimation
par: Kato, Masahiro
Publié: (2024)

Inference in Partially Linear Models under Dependent Data with Deep Neural Networks
par: Brown, Chad
Publié: (2024)