Imagen de Portada

A unified generalization of inverse regression via adaptive column selection

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Jin, Yin, Luo, Wei
Formato:	Preprint
Publicado:	2024
Materias:	Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Tuning parameter selection for the adaptive nuclear norm regularized trace regression
por: Shang, Pan, et al.
Publicado: (2024)

Guiding adaptive shrinkage by co-data to improve regression-based prediction and feature selection
por: van de Wiel, Mark A., et al.
Publicado: (2024)

The $α$--regression for compositional data: a unified framework for standard, temporal and spatial regression models including compositional predictors
por: Tsagris, Michail, et al.
Publicado: (2025)

High-dimensional sliced inverse regression with endogeneity
por: Nghiem, Linh H., et al.
Publicado: (2024)

A comparative study of augmented inverse propensity weighted estimators using outcome-oriented covariate selection via penalization with outcome-adaptive lasso
por: Hongo, Wataru, et al.
Publicado: (2024)

Flexible survival regression with variable selection for heterogeneous population
por: Mandal, Abhishek, et al.
Publicado: (2024)

Estimation, inference and model selection for jump regression models
por: Grønneberg, Steffen, et al.
Publicado: (2026)

Improved LARS algorithm for adaptive LASSO in the linear regression model
por: Kayanan, Manickavasagar, et al.
Publicado: (2024)

Variable selection in balance regression with applications to microbiome compositional data
por: Ma, Jing, et al.
Publicado: (2023)

A comparison of Kaplan--Meier-based inverse probability of censoring weighted regression methods
por: Overgaard, Morten
Publicado: (2024)

Subdata selection for big data regression: an improved approach
por: Chasiotis, Vasilis, et al.
Publicado: (2023)

Functional regression with multivariate responses
por: Luo, Ruiyan, et al.
Publicado: (2026)

Asymptotically-exact selective inference for quantile regression
por: Wang, Yumeng, et al.
Publicado: (2024)

An extended generalized Pareto regression model for count data
por: Ahmad, Touqeer, et al.
Publicado: (2022)

Scalar-on-distribution regression via generalized odds with applications to accelerometry-assessed disability in multiple sclerosis
por: Niyogi, Pratim Guha, et al.
Publicado: (2026)

Quantile regression with generalized multiquadric loss function
por: Gao, Wenwu, et al.
Publicado: (2025)

Bayesian compositional regression with flexible microbiome feature aggregation and selection
por: Saha, Satabdi, et al.
Publicado: (2024)

Post-selection inference in generalized linear models via parametric programming
por: Shen, Qinyan, et al.
Publicado: (2026)

Neural interval-censored survival regression with feature selection
por: Meixide, Carlos García, et al.
Publicado: (2022)

A general, flexible and harmonious framework to construct interpretable functions in regression analysis
por: Zhan, Tianyu, et al.
Publicado: (2025)

Confidence intervals for functionals in constrained inverse problems via data-adaptive sampling-based calibration
por: Stanley, Michael, et al.
Publicado: (2025)

An exhaustive selection of sufficient adjustment sets for causal inference
por: Luo, Wei, et al.
Publicado: (2024)

Confidence intervals for two-stage adaptive designs with subpopulation selection
por: Li, Enyu, et al.
Publicado: (2026)

A general framework for formulating structured variable selection
por: Wang, Guanbo, et al.
Publicado: (2021)

Causal attribution by the chain rule: unifying natural selection, learning, economics, and other disciplines
por: Frank, Steven A.
Publicado: (2026)

Scalable regression calibration approaches to correcting measurement error in multi-level generalized functional linear regression models with heteroscedastic measurement errors
por: Luan, Yuanyuan, et al.
Publicado: (2023)

Safe subspace screening for the adaptive nuclear norm regularized trace regression
por: Shang, Pan, et al.
Publicado: (2024)

Comparison study of variable selection procedures in high-dimensional Gaussian linear regression
por: Lacroix, Perrine, et al.
Publicado: (2021)

A new approach to locally adaptive polynomial regression
por: Chatterjee, Sabyasachi, et al.
Publicado: (2024)

Sandwich regression for accurate and robust estimation in generalized linear multilevel and longitudinal models
por: Young, Elliot H., et al.
Publicado: (2024)

A unified quantile framework for nonlinear heterogeneous transcriptome-wide associations
por: Wang, Tianying, et al.
Publicado: (2022)

Enhanced variable selection for boosting sparser and less complex models in distributional copula regression
por: Strömer, Annika, et al.
Publicado: (2024)

A regression-based approach for bidirectional proximal causal inference in the presence of unmeasured confounding
por: Min, Jiaqi, et al.
Publicado: (2025)

Network-based Neighborhood regression
por: Zhen, Yaoming, et al.
Publicado: (2024)

Inverse regression for causal inference with multiple outcomes
por: Zhang, Wei, et al.
Publicado: (2025)

Density regression via Dirichlet process mixtures of normal structured additive regression models
por: Rodríguez-Álvarez, María Xosé, et al.
Publicado: (2024)

A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression
por: Kim, Youngseok, et al.
Publicado: (2022)

A robust mixed-effects quantile regression model using generalized Laplace mixtures to handle outliers and skewness
por: Burger, Divan A., et al.
Publicado: (2025)

Adversarial learning for nonparametric regression: Minimax rate and adaptive estimation
por: Peng, Jingfu, et al.
Publicado: (2025)

The $\infty$-S test via regression quantile affine LASSO
por: Sardy, Sylvain, et al.
Publicado: (2024)