Pages that link to "Item:Q5743151"

The following pages link to Large Covariance Estimation by Thresholding Principal Orthogonal Complements (Q5743151):

Displaying 50 items.

• Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization (Q5131966) (← links)
• The Five Trolls Under the Bridge: Principal Component Analysis With Asynchronous and Noisy High Frequency Data (Q5146046) (← links)
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• (Q5159462) (← links)
• (Q5159467) (← links)
• Statistical inference for the tangency portfolio in high dimension (Q5163043) (← links)
• Forecasting Multiple Time Series With One-Sided Dynamic Principal Components (Q5208073) (← links)
• FarmTest: Factor-Adjusted Robust Multiple Testing With Approximate False Discovery Control (Q5208092) (← links)
• Tuning-parameter selection in regularized estimations of large covariance matrices (Q5222349) (← links)
• Large Covariance Estimation for Compositional Data Via Composition-Adjusted Thresholding (Q5231504) (← links)
• Graph-Guided Banding of the Covariance Matrix (Q5231506) (← links)
• Factor and Idiosyncratic Empirical Processes (Q5242464) (← links)
• Sparse Covariance Matrix Estimation by DCA-Based Algorithms (Q5380866) (← links)
• TESTING FOR STRUCTURAL CHANGES IN FACTOR MODELS VIA A NONPARAMETRIC REGRESSION (Q5859565) (← links)
• Spiked sample covariance matrices with possibly multiple bulk components (Q5860230) (← links)
• Testing for time-varying factor loadings in high-dimensional factor models (Q5867577) (← links)
• Multiple Anchor Point Shrinkage for the Sample Covariance Matrix (Q5868799) (← links)
• Factor Extraction in Dynamic Factor Models: Kalman Filter Versus Principal Components (Q5870780) (← links)
• Model-Free Feature Screening and FDR Control With Knockoff Features (Q5881096) (← links)
• Modeling High-Dimensional Time Series: A Factor Model With Dynamically Dependent Factors and Diverging Eigenvalues (Q5881144) (← links)
• Estimating Number of Factors by Adjusted Eigenvalues Thresholding (Q5885109) (← links)
• Learning Latent Factors From Diversified Projections and Its Applications to Over-Estimated and Weak Factors (Q5885115) (← links)
• High-Dimensional Factor Regression for Heterogeneous Subpopulations (Q6039856) (← links)
• Statistical quality control using image intelligence: A sparse learning approach (Q6051603) (← links)
• On variable ordination of Cholesky‐based estimation for a sparse covariance matrix (Q6059504) (← links)
• Sampling distributions of optimal portfolio weights and characteristics in small and large dimensions (Q6063734) (← links)
• A new approach for ultrahigh-dimensional covariance matrix estimation (Q6067019) (← links)
• On Generalized Latent Factor Modeling and Inference for High-Dimensional Binomial Data (Q6079715) (← links)
• Penalized Regression for Multiple Types of Many Features With Missing Data (Q6086158) (← links)
• Adaptive robust large volatility matrix estimation based on high-frequency financial data (Q6090556) (← links)
• Dynamic factor copula models with estimated cluster assignments (Q6090586) (← links)
• Cross-Validated Loss-based Covariance Matrix Estimator Selection in High Dimensions (Q6094089) (← links)
• Estimation of the Number of Spiked Eigenvalues in a Covariance Matrix by Bulk Eigenvalue Matching Analysis (Q6107215) (← links)
• Correlation Tensor Decomposition and Its Application in Spatial Imaging Data (Q6107220) (← links)
• Sharpe ratio analysis in high dimensions: residual-based nodewise regression in factor models (Q6108258) (← links)
• Community network auto-regression for high-dimensional time series (Q6108298) (← links)
• Parametric estimation of long memory in factor models (Q6108311) (← links)
• Binary response models for heterogeneous panel data with interactive fixed effects (Q6108322) (← links)
• Large volatility matrix analysis using global and national factor models (Q6108334) (← links)
• Integrative Factor Regression and Its Inference for Multimodal Data Analysis (Q6110734) (← links)
• Block-diagonal precision matrix regularization for ultra-high dimensional data (Q6111505) (← links)
• Bayesian sparse spiked covariance model with a continuous matrix shrinkage prior (Q6121981) (← links)
• Post-processed posteriors for sparse covariances (Q6133369) (← links)
• Factor models for high‐dimensional functional time series I: Representation results (Q6135371) (← links)
• Factor models for high‐dimensional functional time series II: Estimation and forecasting (Q6135372) (← links)
• Optimal discriminant analysis in high-dimensional latent factor models (Q6136589) (← links)
• Matrix-variate data analysis by two-way factor model with replicated observations (Q6137835) (← links)
• On determination of the number of factors in an approximate factor model (Q6138244) (← links)
• A One-Sided Refined Symmetrized Data Aggregation Approach to Robust Mutual Fund Selection (Q6150363) (← links)
• Matrix Factor Analysis: From Least Squares to Iterative Projection (Q6150367) (← links)