Pages that link to "Item:Q2477058"
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The following pages link to Regularized estimation of large covariance matrices (Q2477058):
Displaying 50 items.
- A permutation-based Bayesian approach for inverse covariance estimation (Q5077443) (← links)
- Rates of convergence in conditional covariance matrix with nonparametric entries estimation (Q5077524) (← links)
- (Q5089457) (← links)
- Fast Bayesian variable screenings for binary response regressions with small sample size (Q5106969) (← links)
- LARGE SYSTEM OF SEEMINGLY UNRELATED REGRESSIONS: A PENALIZED QUASI-MAXIMUM LIKELIHOOD ESTIMATION PERSPECTIVE (Q5112017) (← links)
- Analysis of a localised nonlinear ensemble Kalman Bucy filter with complete and accurate observations (Q5130910) (← links)
- Joint Bayesian Variable and DAG Selection Consistency for High-dimensional Regression Models with Network-structured Covariates (Q5155198) (← links)
- Computational and statistical tradeoffs via convex relaxation (Q5170958) (← links)
- Trimmed estimators for large dimensional sparse covariance matrices (Q5197365) (← links)
- Tuning-parameter selection in regularized estimations of large covariance matrices (Q5222349) (← links)
- Graph-Guided Banding of the Covariance Matrix (Q5231506) (← links)
- Testing for Trends in High-Dimensional Time Series (Q5231513) (← links)
- Sparse Minimum Discrepancy Approach to Sufficient Dimension Reduction with Simultaneous Variable Selection in Ultrahigh Dimension (Q5242475) (← links)
- Smooth monotone covariance for elliptical distributions and applications in finance (Q5245911) (← links)
- Estimation of a sparse and spiked covariance matrix (Q5256289) (← links)
- Simultaneous sparse model selection and coefficient estimation for heavy-tailed autoregressive processes (Q5263975) (← links)
- Clustering High-Dimensional Time Series Based on Parallelism (Q5327288) (← links)
- A DC Programming Approach for Sparse Estimation of a Covariance Matrix (Q5356977) (← links)
- Asymptotic distribution of least square estimators for linear models with dependent errors (Q5384673) (← links)
- An accurate test for the equality of covariance matrices from decomposable graphical Gaussian models (Q5413639) (← links)
- A sequential scaled pairwise selection approach to edge detection in nonparanormal graphical models (Q5507345) (← links)
- Correlation structure selection for longitudinal data with diverging cluster size (Q5507362) (← links)
- Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models (Q5743269) (← links)
- Random matrix improved covariance estimation for a large class of metrics* (Q5857459) (← links)
- The impact of jumps and leverage in forecasting covolatility (Q5864641) (← links)
- An improved banded estimation for large covariance matrix (Q5875206) (← links)
- Covariance estimation via fiducial inference (Q5880096) (← links)
- On the non-local priors for sparsity selection in high-dimensional Gaussian DAG models (Q5880097) (← links)
- Variable screening in multivariate linear regression with high-dimensional covariates (Q5880134) (← links)
- Cholesky-based model averaging for covariance matrix estimation (Q5880164) (← links)
- Factor analysis of correlation matrices when the number of random variables exceeds the sample size (Q5880184) (← links)
- AdaBoost Semiparametric Model Averaging Prediction for Multiple Categories (Q5881103) (← links)
- Covariate Information Number for Feature Screening in Ultrahigh-Dimensional Supervised Problems (Q5881153) (← links)
- Convergence and finite sample approximations of entropic regularized Wasserstein distances in Gaussian and RKHS settings (Q5889893) (← links)
- Estimating structured high-dimensional covariance and precision matrices: optimal rates and adaptive estimation (Q5965313) (← links)
- Discussion: Latent variable graphical model selection via convex optimization (Q5970644) (← links)
- Discussion: Latent variable graphical model selection via convex optimization (Q5970645) (← links)
- Discussion: Latent variable graphical model selection via convex optimization (Q5970646) (← links)
- Discussion: Latent variable graphical model selection via convex optimization (Q5970647) (← links)
- Discussion: Latent variable graphical model selection via convex optimization (Q5970648) (← links)
- Frequentist Model Averaging for the Nonparametric Additive Model (Q6039882) (← links)
- Learning Gaussian graphical models with latent confounders (Q6051077) (← links)
- A random covariance model for bi‐level graphical modeling with application to resting‐state fMRI data (Q6055494) (← links)
- Cellwise outlier detection with false discovery rate control (Q6059406) (← links)
- A new approach for ultrahigh-dimensional covariance matrix estimation (Q6067019) (← links)
- A quantile‐slicing approach for sufficient dimension reduction with censored responses (Q6067320) (← links)
- Adaptive Tests for Bandedness of High-dimensional Covariance Matrices (Q6069890) (← links)
- Covariance structure estimation with Laplace approximation (Q6074739) (← links)
- Model-Based Clustering of High-Dimensional Longitudinal Data via Regularization (Q6079763) (← links)
- Hypothesis Testing of Matrix Graph Model with Application to Brain Connectivity Analysis (Q6079973) (← links)
