Pages that link to "Item:Q4904725"
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The following pages link to Positive-Definite ℓ<sub>1</sub>-Penalized Estimation of Large Covariance Matrices (Q4904725):
Displaying 50 items.
- Adaptive estimation of the copula correlation matrix for semiparametric elliptical copulas (Q265300) (← links)
- Regularization for high-dimensional covariance matrix (Q287603) (← links)
- Positive semidefiniteness of estimated covariance matrices in linear models for sample survey data (Q287607) (← links)
- Ensemble sparse estimation of covariance structure for exploring genetic disease data (Q830118) (← links)
- Efficient estimation of approximate factor models via penalized maximum likelihood (Q898581) (← links)
- A sequential test for variable selection in high dimensional complex data (Q1623732) (← links)
- High dimensional covariance matrix estimation by penalizing the matrix-logarithm transformed likelihood (Q1658345) (← links)
- Sparse estimation of high-dimensional correlation matrices (Q1660228) (← links)
- Sparse Markowitz portfolio selection by using stochastic linear complementarity approach (Q1716964) (← links)
- An implementable first-order primal-dual algorithm for structured convex optimization (Q1724030) (← links)
- A multiple testing approach to the regularisation of large sample correlation matrices (Q1739875) (← links)
- Covariance estimation via sparse Kronecker structures (Q1750103) (← links)
- Weighted covariance matrix estimation (Q2002720) (← links)
- Estimation and optimal structure selection of high-dimensional Toeplitz covariance matrix (Q2034455) (← links)
- Positive-definite modification of a covariance matrix by minimizing the matrix \(\ell_{\infty}\) norm with applications to portfolio optimization (Q2068898) (← links)
- Fourier transform sparse inverse regression estimators for sufficient variable selection (Q2076139) (← links)
- High-performance statistical computing in the computing environments of the 2020s (Q2092893) (← links)
- An efficient numerical method for condition number constrained covariance matrix approximation (Q2242067) (← links)
- Spatial disease mapping using directed acyclic graph auto-regressive (DAGAR) models (Q2290712) (← links)
- Alternating proximal gradient method for convex minimization (Q2399191) (← links)
- On the penalized maximum likelihood estimation of high-dimensional approximate factor model (Q2418076) (← links)
- D-trace estimation of a precision matrix using adaptive lasso penalties (Q2418368) (← links)
- Fixed support positive-definite modification of covariance matrix estimators via linear shrinkage (Q2418516) (← links)
- Sparse and low-rank covariance matrix estimation (Q2516376) (← links)
- On the existence of positive-definite maximum-likelihood estimates of structured covariance matrices (Q3810694) (← links)
- Estimation of Graphical Models through Structured Norm Minimization (Q4558541) (← links)
- A Cholesky-based estimation for large-dimensional covariance matrices (Q5037036) (← links)
- Gaussian Patch Mixture Model Guided Low-Rank Covariance Matrix Minimization for Image Denoising (Q5056914) (← links)
- A dual active-set proximal Newton algorithm for sparse approximation of correlation matrices (Q5058396) (← links)
- Diagonally Dominant Principal Component Analysis (Q5066006) (← links)
- A graphical model selection tool for mixed models (Q5085047) (← links)
- High-dimensional Markowitz portfolio optimization problem: empirical comparison of covariance matrix estimators (Q5107390) (← links)
- HIGHER-ORDER ACCURATE, POSITIVE SEMIDEFINITE ESTIMATION OF LARGE-SAMPLE COVARIANCE AND SPECTRAL DENSITY MATRICES (Q5199496) (← links)
- Double shrinkage estimators for large sparse covariance matrices (Q5220803) (← links)
- Tuning-parameter selection in regularized estimations of large covariance matrices (Q5222349) (← links)
- Some Statistical Problems with High Dimensional Financial data (Q5227362) (← links)
- Graph-Guided Banding of the Covariance Matrix (Q5231506) (← links)
- Sparse Minimum Discrepancy Approach to Sufficient Dimension Reduction with Simultaneous Variable Selection in Ultrahigh Dimension (Q5242475) (← links)
- Estimation of a sparse and spiked covariance matrix (Q5256289) (← links)
- Alternating Direction Methods for Latent Variable Gaussian Graphical Model Selection (Q5378251) (← links)
- Sparse Covariance Matrix Estimation by DCA-Based Algorithms (Q5380866) (← links)
- Correlation structure selection for longitudinal data with diverging cluster size (Q5507362) (← links)
- Conditioning theory of the equality constrained quadratic programming and its applications (Q5858718) (← links)
- An improved banded estimation for large covariance matrix (Q5875206) (← links)
- Cholesky-based model averaging for covariance matrix estimation (Q5880164) (← links)
- A Compound Decision Approach to Covariance Matrix Estimation (Q6055869) (← links)
- On variable ordination of Cholesky‐based estimation for a sparse covariance matrix (Q6059504) (← links)
- Robust Shape Matrix Estimation for High-Dimensional Compositional Data with Application to Microbial Inter-Taxa Analysis (Q6069886) (← links)
- Testing and signal identification for two-sample high-dimensional covariances via multi-level thresholding (Q6108302) (← links)
- Power enhancement for testing multi-factor asset pricing models via Fisher's method (Q6150526) (← links)
