Design-based finite-sample analysis for regression adjustment
Fuente:
arXiv
Guardado en:
| Autor principal: | Song, Dogyoon |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Neumann-series corrections for regression adjustment in randomized experiments
por: Song, Dogyoon
Publicado: (2025)
por: Song, Dogyoon
Publicado: (2025)
Debiased regression adjustment in completely randomized experiments with moderately high-dimensional covariates
por: Lu, Xin, et al.
Publicado: (2023)
por: Lu, Xin, et al.
Publicado: (2023)
Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator
por: Shen, Dennis, et al.
Publicado: (2023)
por: Shen, Dennis, et al.
Publicado: (2023)
Design-based theory for Lasso adjustment in randomized block experiments and rerandomized experiments
por: Zhu, Ke, et al.
Publicado: (2021)
por: Zhu, Ke, et al.
Publicado: (2021)
Multivariate and Multiple Contrast Testing in General Covariate-adjusted Factorial Designs
por: Baumeister, Marléne, et al.
Publicado: (2025)
por: Baumeister, Marléne, et al.
Publicado: (2025)
Finite sample-optimal adjustment sets in linear Gaussian causal models
por: Rutsch, Nadja, et al.
Publicado: (2025)
por: Rutsch, Nadja, et al.
Publicado: (2025)
Shape-restricted transfer learning analysis for generalized linear regression model
por: Li, Pengfei, et al.
Publicado: (2024)
por: Li, Pengfei, et al.
Publicado: (2024)
On Separability of Covariance in Multiway Data Analysis
por: Song, Dogyoon, et al.
Publicado: (2023)
por: Song, Dogyoon, et al.
Publicado: (2023)
Bayesian change-plane regression
por: Ohnishi, Yuki, et al.
Publicado: (2026)
por: Ohnishi, Yuki, et al.
Publicado: (2026)
Regression adjustment in covariate-adaptive randomized experiments with missing covariates
por: Fu, Wanjia, et al.
Publicado: (2025)
por: Fu, Wanjia, et al.
Publicado: (2025)
On the achievability of efficiency bounds for covariate-adjusted response-adaptive randomization
por: Xin, Jiahui, et al.
Publicado: (2024)
por: Xin, Jiahui, et al.
Publicado: (2024)
Difference-based covariance matrix estimate in time series nonparametric regression with applications to specification tests
por: Bai, Lujia, et al.
Publicado: (2023)
por: Bai, Lujia, et al.
Publicado: (2023)
Optimal heteroskedasticity testing in nonparametric regression
por: Kotekal, Subhodh, et al.
Publicado: (2023)
por: Kotekal, Subhodh, et al.
Publicado: (2023)
Unifying regression-based and design-based causal inference in time-series experiments
por: Lin, Zhexiao, et al.
Publicado: (2025)
por: Lin, Zhexiao, et al.
Publicado: (2025)
Regularized zero-inflated Bernoulli regression model
por: Ndoye, Mouhamed, et al.
Publicado: (2025)
por: Ndoye, Mouhamed, et al.
Publicado: (2025)
Nonparametric quantile regression for spatio-temporal processes
por: Deb, Soudeep, et al.
Publicado: (2024)
por: Deb, Soudeep, et al.
Publicado: (2024)
Fusion regression methods with repeated functional data
por: Moindjié, Issam-Ali, et al.
Publicado: (2023)
por: Moindjié, Issam-Ali, et al.
Publicado: (2023)
Asymptotically-exact selective inference for quantile regression
por: Wang, Yumeng, et al.
Publicado: (2024)
por: Wang, Yumeng, et al.
Publicado: (2024)
Bayesian $L_{\frac{1}{2}}$ regression
por: Ke, Xiongwen, et al.
Publicado: (2021)
por: Ke, Xiongwen, et al.
Publicado: (2021)
Residual permutation test for regression coefficient testing
por: Wen, Kaiyue, et al.
Publicado: (2022)
por: Wen, Kaiyue, et al.
Publicado: (2022)
High-dimensional regression with a count response
por: Zilberman, Or, et al.
Publicado: (2024)
por: Zilberman, Or, et al.
Publicado: (2024)
Deep neural expected shortfall regression with tail-robustness
por: Yu, Myeonghun, et al.
Publicado: (2025)
por: Yu, Myeonghun, et al.
Publicado: (2025)
A multivariate spatial regression model using signatures
por: Frévent, Camille, et al.
Publicado: (2024)
por: Frévent, Camille, et al.
Publicado: (2024)
Testing for no effect in regression problems: a permutation approach
por: Ciszewski, Michał, et al.
Publicado: (2023)
por: Ciszewski, Michał, et al.
Publicado: (2023)
Gaussian and bootstrap approximations for functional principal component regression
por: Yeon, Hyemin
Publicado: (2026)
por: Yeon, Hyemin
Publicado: (2026)
Asymptotic properties of the MLE in distributional regression under random censoring
por: Kremling, Gitte, et al.
Publicado: (2025)
por: Kremling, Gitte, et al.
Publicado: (2025)
Valid and efficient possibilistic structure learning in Gaussian linear regression
por: Martin, Ryan, et al.
Publicado: (2025)
por: Martin, Ryan, et al.
Publicado: (2025)
Series ridge regression for spatial data on $\mathbb{R}^d$
por: Kurisu, Daisuke, et al.
Publicado: (2024)
por: Kurisu, Daisuke, et al.
Publicado: (2024)
Sufficient dimension reduction for regression with spatially correlated errors: application to prediction
por: Forzani, Liliana, et al.
Publicado: (2025)
por: Forzani, Liliana, et al.
Publicado: (2025)
Inference for function-on-function regression: central limit theorem and residual bootstrap
por: Yeon, Hyemin
Publicado: (2026)
por: Yeon, Hyemin
Publicado: (2026)
logitFD: an R package for functional principal component logit regression
por: Escabias, Manuel, et al.
Publicado: (2024)
por: Escabias, Manuel, et al.
Publicado: (2024)
Self-convolved Bootstrap for M-regression under Complex Temporal Dynamics
por: Liu, Miaoshiqi, et al.
Publicado: (2023)
por: Liu, Miaoshiqi, et al.
Publicado: (2023)
Improved confidence intervals for nonlinear mixed-effects and nonparametric regression models
por: Zheng, Nan, et al.
Publicado: (2024)
por: Zheng, Nan, et al.
Publicado: (2024)
Optimal Cox regression under federated differential privacy: coefficients and cumulative hazards
por: Hung, Elly K. H., et al.
Publicado: (2025)
por: Hung, Elly K. H., et al.
Publicado: (2025)
Detection and inference of changes in high-dimensional linear regression with non-sparse structures
por: Cho, Haeran, et al.
Publicado: (2024)
por: Cho, Haeran, et al.
Publicado: (2024)
Simultaneous Inference for Nonlinear Time Series, a Sieve M-regression Approach
por: Luo, Tianpai, et al.
Publicado: (2026)
por: Luo, Tianpai, et al.
Publicado: (2026)
Valid F-screening in linear regression
por: McGough, Olivia, et al.
Publicado: (2025)
por: McGough, Olivia, et al.
Publicado: (2025)
IV regression with distribution-valued outcomes
por: Van Dijcke, David, et al.
Publicado: (2026)
por: Van Dijcke, David, et al.
Publicado: (2026)
Capturing heterogeneous time-variation in covariate effects in non-proportional hazard regression models
por: Hagemann, Niklas, et al.
Publicado: (2025)
por: Hagemann, Niklas, et al.
Publicado: (2025)
Fitting sparse high-dimensional varying-coefficient models with Bayesian regression tree ensembles
por: Ghosh, Soham, et al.
Publicado: (2025)
por: Ghosh, Soham, et al.
Publicado: (2025)
Ejemplares similares
-
Neumann-series corrections for regression adjustment in randomized experiments
por: Song, Dogyoon
Publicado: (2025) -
Debiased regression adjustment in completely randomized experiments with moderately high-dimensional covariates
por: Lu, Xin, et al.
Publicado: (2023) -
Algebraic and Statistical Properties of the Ordinary Least Squares Interpolator
por: Shen, Dennis, et al.
Publicado: (2023) -
Design-based theory for Lasso adjustment in randomized block experiments and rerandomized experiments
por: Zhu, Ke, et al.
Publicado: (2021) -
Multivariate and Multiple Contrast Testing in General Covariate-adjusted Factorial Designs
por: Baumeister, Marléne, et al.
Publicado: (2025)