High-dimensional covariance matrix regularization using informative targets
Fuente:
arXiv
Saved in:
| Main Authors: | Rehman, Atiq Ur, Farooq, Muhammad |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Testing for large-dimensional covariance matrix under differential privacy
by: Sang, Shiwei, et al.
Published: (2025)
by: Sang, Shiwei, et al.
Published: (2025)
Robust regularized covariance matrix estimation: well-posedness and convergent algorithm
by: Yi, Mengxi, et al.
Published: (2026)
by: Yi, Mengxi, et al.
Published: (2026)
High dimensional test for functional covariates
by: Jin, Huaqing, et al.
Published: (2024)
by: Jin, Huaqing, et al.
Published: (2024)
Doubly regularized generalized linear models for spatial observations with high-dimensional covariates
by: Sondhi, Arjun, et al.
Published: (2024)
by: Sondhi, Arjun, et al.
Published: (2024)
Optimal covariance matrix estimation for high-dimensional noise in high-frequency data
by: Chang, Jinyuan, et al.
Published: (2018)
by: Chang, Jinyuan, et al.
Published: (2018)
Change-point detection in variance-covariance matrix
by: Lin, Ying, et al.
Published: (2026)
by: Lin, Ying, et al.
Published: (2026)
Transportable inference using target population summary statistics under covariate shift
by: Sheng, Ying, et al.
Published: (2026)
by: Sheng, Ying, et al.
Published: (2026)
Online robust covariance matrix estimation and outlier detection
by: Guillot, Paul, et al.
Published: (2026)
by: Guillot, Paul, et al.
Published: (2026)
Direct covariance matrix estimation with compositional data
by: Molstad, Aaron J., et al.
Published: (2022)
by: Molstad, Aaron J., et al.
Published: (2022)
High-dimensional covariance regression with application to co-expression QTL detection
by: Kim, Rakheon, et al.
Published: (2024)
by: Kim, Rakheon, et al.
Published: (2024)
Highly robust factored principal component analysis for matrix-valued outlier accommodation and explainable detection via matrix minimum covariance determinant
by: Wu, Wenhui, et al.
Published: (2025)
by: Wu, Wenhui, et al.
Published: (2025)
A covariate-dependent Cholesky decomposition for high-dimensional covariance regression
by: Kim, Rakheon, et al.
Published: (2026)
by: Kim, Rakheon, et al.
Published: (2026)
Nonparametric regression of spatio-temporal data using infinite-dimensional covariates
by: Roy, Subhrajyoty, et al.
Published: (2026)
by: Roy, Subhrajyoty, et al.
Published: (2026)
Large covariance matrix estimation with factor-assisted variable clustering
by: Li, Dong, et al.
Published: (2025)
by: Li, Dong, et al.
Published: (2025)
Applying non-negative matrix factorization with covariates to label matrix for classification
by: Satoh, Kenichi
Published: (2025)
by: Satoh, Kenichi
Published: (2025)
Modeling the uncertainty on the covariance matrix for probabilistic forecast reconciliation
by: Carrara, Chiara, et al.
Published: (2025)
by: Carrara, Chiara, et al.
Published: (2025)
High dimensional matrix estimation through elliptical factor models
by: Xu, Xinyue, et al.
Published: (2025)
by: Xu, Xinyue, et al.
Published: (2025)
Minimum regularized covariance trace estimator and outlier detection for functional data
by: Oguamalam, Jeremy, et al.
Published: (2023)
by: Oguamalam, Jeremy, et al.
Published: (2023)
Asymptotic testing of covariance separability for matrix elliptical data
by: Virta, Joni, et al.
Published: (2026)
by: Virta, Joni, et al.
Published: (2026)
Posterior covariance information criterion for general loss functions
by: Iba, Yukito, et al.
Published: (2022)
by: Iba, Yukito, et al.
Published: (2022)
Factor-guided estimation of large covariance matrix function with conditional functional sparsity
by: Li, Dong, et al.
Published: (2023)
by: Li, Dong, et al.
Published: (2023)
Robust covariance estimation and explainable outlier detection for matrix-valued data
by: Mayrhofer, Marcus, et al.
Published: (2024)
by: Mayrhofer, Marcus, et al.
Published: (2024)
High-dimensional low-rank matrix regression with unknown latent structures
by: Wang, Di, et al.
Published: (2025)
by: Wang, Di, et al.
Published: (2025)
Simultaneous global and local clustering in multiplex networks with covariate information
by: Corneck, Joshua, et al.
Published: (2025)
by: Corneck, Joshua, et al.
Published: (2025)
Model-based bi-clustering using multivariate Poisson-lognormal with general block-diagonal covariance matrix and its applications
by: Kral, Caitlin, et al.
Published: (2025)
by: Kral, Caitlin, et al.
Published: (2025)
HIMCE: High-dimensional multiple imputation via covariance-mode updating for neuroimaging and spatiotemporal blocks
by: Huang, Hsin-Hsiung, et al.
Published: (2026)
by: Huang, Hsin-Hsiung, et al.
Published: (2026)
Rank-based Bayesian clustering via covariate-informed Mallows mixtures
by: Eliseussen, Emilie, et al.
Published: (2023)
by: Eliseussen, Emilie, et al.
Published: (2023)
NExON-Bayes: A Bayesian approach to network estimation informed by ordinal covariates
by: Feest, Joseph, et al.
Published: (2025)
by: Feest, Joseph, et al.
Published: (2025)
A regularized multi-state model for covariate selection with interval-censored survival data
by: Bercu, Ariane, et al.
Published: (2025)
by: Bercu, Ariane, et al.
Published: (2025)
Applying non-negative matrix factorization with covariates to multivariate time series data as a vector autoregression model
by: Satoh, Kenichi
Published: (2025)
by: Satoh, Kenichi
Published: (2025)
Data adaptive covariate balancing for causal effect estimation for high dimensional data
by: De, Simion, et al.
Published: (2025)
by: De, Simion, et al.
Published: (2025)
A lack-of-fit test for quantile regression models with high-dimensional covariates
by: Conde-Amboage, Mercedes, et al.
Published: (2015)
by: Conde-Amboage, Mercedes, et al.
Published: (2015)
Integrative data analysis where partial covariates have complex non-linear effects by using summary information from an external data
by: Liang, Jia, et al.
Published: (2023)
by: Liang, Jia, et al.
Published: (2023)
A Markov-switching dynamic matrix factor model for the high-dimensional matrix time series
by: Yuan, Chaofeng, et al.
Published: (2025)
by: Yuan, Chaofeng, et al.
Published: (2025)
When Bayes goes bad: Weakly-regularized covariate adjustment leads to a biased estimate of prevalence
by: Kuh, Swen, et al.
Published: (2026)
by: Kuh, Swen, et al.
Published: (2026)
Difference-based covariance matrix estimate in time series nonparametric regression with applications to specification tests
by: Bai, Lujia, et al.
Published: (2023)
by: Bai, Lujia, et al.
Published: (2023)
Low-rank matrix estimation via nonconvex spectral regularized methods in errors-in-variables matrix regression
by: Li, Xin, et al.
Published: (2024)
by: Li, Xin, et al.
Published: (2024)
Causal machine learning for high-dimensional mediation analysis using interventional effects mapped to a target trial
by: Chen, Tong, et al.
Published: (2025)
by: Chen, Tong, et al.
Published: (2025)
Estimating the variance-covariance matrix of two-step estimates of latent variable models: A general simulation-based approach
by: Di Mari, Roberto, et al.
Published: (2025)
by: Di Mari, Roberto, et al.
Published: (2025)
General Bayesian inference for causal effects using covariate balancing procedure
by: Orihara, Shunichiro, et al.
Published: (2024)
by: Orihara, Shunichiro, et al.
Published: (2024)
Similar Items
-
Testing for large-dimensional covariance matrix under differential privacy
by: Sang, Shiwei, et al.
Published: (2025) -
Robust regularized covariance matrix estimation: well-posedness and convergent algorithm
by: Yi, Mengxi, et al.
Published: (2026) -
High dimensional test for functional covariates
by: Jin, Huaqing, et al.
Published: (2024) -
Doubly regularized generalized linear models for spatial observations with high-dimensional covariates
by: Sondhi, Arjun, et al.
Published: (2024) -
Optimal covariance matrix estimation for high-dimensional noise in high-frequency data
by: Chang, Jinyuan, et al.
Published: (2018)