Imagen de Portada

High-Dimensional Multi-Study Multi-Modality Covariate-Augmented Generalized Factor Model

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Liu, Wei, Zhong, Qingzhi
Formato:	Preprint
Publicado:	2025
Materias:	Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

High-Dimensional Covariate-Augmented Overdispersed Multi-Study Poisson Factor Model
por: Liu, Wei, et al.
Publicado: (2024)

High-Dimensional Covariate-Augmented Overdispersed Poisson Factor Model
por: Liu, Wei, et al.
Publicado: (2024)

Inference on Generalized Latent Variable Models with High-Dimensional Responses and Covariates
por: Ouyang, Jing, et al.
Publicado: (2026)

High-Dimensional Covariate-Dependent Gaussian Graphical Models
por: Wang, Jiacheng, et al.
Publicado: (2025)

High-Dimensional Overdispersed Generalized Factor Model with Application to Single-Cell Sequencing Data Analysis
por: Nie, Jinyu, et al.
Publicado: (2024)

Robust High-Dimensional Covariate-Assisted Network Modeling
por: Zhao, Peng, et al.
Publicado: (2025)

A Time-Varying and Covariate-Dependent Correlation Model for Multivariate Longitudinal Studies
por: Liu, Qingzhi, et al.
Publicado: (2026)

Covariance Function Estimation for High-Dimensional Functional Time Series with Dual Factor Structures
por: Leng, Chenlei, et al.
Publicado: (2024)

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

Adaptive Multi-Prior Lasso for High-Dimensional Generalized Linear Models
por: Xu, Fuzhi, et al.
Publicado: (2026)

Covariance Matrix Estimation for High-Dimensional Interval-Valued Data with Positive Definiteness
por: Tian, Wan, et al.
Publicado: (2026)

Inferring High-Dimensional Dynamic Networks Changing with Multiple Covariates
por: Dijkstra, Louis, et al.
Publicado: (2024)

Testing Separability of High-Dimensional Covariance Matrices
por: Sung, Bongjung, et al.
Publicado: (2025)

Bayesian Covariance Structure Modeling of Multi-Way Nested Data
por: Baas, Stef, et al.
Publicado: (2022)

High-Dimensional Covariate-Dependent Discrete Graphical Models and Dynamic Ising Models
por: Roach, Lyndsay, et al.
Publicado: (2025)

Optimal Network-Guided Covariate Selection for High-Dimensional Data Integration
por: Shen, Tao, et al.
Publicado: (2025)

Factorized Tail Volatility Model: Augmenting Excess-over-Threshold Method for High-Dimensional Hevay-Tailed Data
por: Hu, Yifan, et al.
Publicado: (2025)

Difference-Based High-Dimensional Long-Run Covariance Matrix Estimation for Mean-shift Time Series
por: Liu, Yanhong, et al.
Publicado: (2026)

Regularized Estimation of the Loading Matrix in Factor Models for High-Dimensional Time Series
por: Liu, Xialu, et al.
Publicado: (2025)

Parametric Modal Regression with Error in Covariates
por: Liu, Qingyang, et al.
Publicado: (2022)

Bayesian Estimation of Propensity Scores for Integrating Multiple Cohorts with High-Dimensional Covariates
por: Guha, Subharup, et al.
Publicado: (2023)

Associating High-Dimensional Longitudinal Datasets through an Efficient Cross-Covariance Decomposition
por: Tan, Jianbin, et al.
Publicado: (2026)

Statistical Inference for Covariate-Adjusted and Interpretable Generalized Factor Model with Application to Testing Fairness
por: Ouyang, Jing, et al.
Publicado: (2024)

Localization Estimator for High Dimensional Tensor Covariance Matrices
por: Sun, Hao-Xuan, et al.
Publicado: (2026)

Robust Covariate Adjustment in Multi-Center Randomized Trials
por: Alene, Muluneh, et al.
Publicado: (2025)

Penalized Sparse Covariance Regression with High Dimensional Covariates
por: Gao, Yuan, et al.
Publicado: (2024)

Sparse-Group Factor Analysis for High-Dimensional Time Series
por: Wang, Xin, et al.
Publicado: (2025)

A Latent Factor Model for High-Dimensional Binary Data
por: Shi, Jiaxin, et al.
Publicado: (2024)

Scalable Dirichlet Process Mixture Models with Unknown Concentration and Adaptive Covariance for High-Dimensional Clustering Applied to Leukemia Transcriptomics
por: Pal, Annesh, et al.
Publicado: (2026)

Bayesian Covariance Estimation for Multi-group Matrix-variate Data
por: Bersson, Elizabeth, et al.
Publicado: (2023)

Multi-Task Learning for High-Dimensional Regression with Many Weak Instruments
por: Zhang, Di, et al.
Publicado: (2025)

Dynamic Matrix Factor Models for High Dimensional Time Series
por: Yu, Ruofan, et al.
Publicado: (2024)

SPARKLE: A Nonparametric Approach for Online Decision-Making with High-Dimensional Covariates
por: Wang, Wenjia, et al.
Publicado: (2025)

High-Dimensional Block Diagonal Covariance Structure Detection Using Singular Vectors
por: Bauer, Jan O.
Publicado: (2022)

Efficient Computation of High-Dimensional Penalized Generalized Linear Mixed Models by Latent Factor Modeling of the Random Effects
por: Heiling, Hillary M., et al.
Publicado: (2023)

Testing Alpha in High Dimensional Linear Factor Pricing Models with Dependent Observations
por: Ma, Huifang, et al.
Publicado: (2024)

Adaptive Strategy of Testing Alphas in High Dimensional Linear Factor Pricing Models
por: Zhao, Chenxi, et al.
Publicado: (2024)

Symmetry-Aware Convex Shrinkage for High-Dimensional Covariance Estimation
por: Thornton, Mitchell A.
Publicado: (2026)

Covariate-moderated Empirical Bayes Matrix Factorization
por: Denault, William R. P., et al.
Publicado: (2025)

Missingness-Adaptive Factor Identification in High-Dimensional Data
por: Zeng, Ping, et al.
Publicado: (2026)