Pages that link to "Item:Q149570"
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The following pages link to Nonlinear shrinkage estimation of large-dimensional covariance matrices (Q149570):
Displaying 50 items.
- Estimation of the global minimum variance portfolio in high dimensions (Q90168) (← links)
- Geometric median and robust estimation in Banach spaces (Q122792) (← links)
- On generating random Gaussian graphical models (Q135242) (← links)
- A well-conditioned estimator for large-dimensional covariance matrices (Q149569) (← links)
- Nonlinear shrinkage estimation of large-dimensional covariance matrices (Q149570) (← links)
- xdcclarge (Q149572) (← links)
- Direct shrinkage estimation of large dimensional precision matrix (Q268760) (← links)
- Estimation of a high-dimensional covariance matrix with the Stein loss (Q276961) (← links)
- Efficient compression of distributed information in estimation fusion (Q283728) (← links)
- Nonparametric eigenvalue-regularized precision or covariance matrix estimator (Q292867) (← links)
- Adaptive shrinkage of singular values (Q294253) (← links)
- Linear shrinkage estimation of large covariance matrices using factor models (Q321913) (← links)
- A regularized profile likelihood approach to covariance matrix estimation (Q334313) (← links)
- Large dimensional analysis and optimization of robust shrinkage covariance matrix estimators (Q406518) (← links)
- Estimating high dimensional covariance matrices: a new look at the Gaussian conjugate framework (Q406528) (← links)
- On the maximum likelihood estimation of a covariance matrix (Q722606) (← links)
- Does Bitcoin add value to global industry portfolios? (Q777646) (← links)
- Improved shrinkage estimator of large-dimensional covariance matrix under the complex Gaussian distribution (Q782294) (← links)
- Efficient estimation of approximate factor models via penalized maximum likelihood (Q898581) (← links)
- Estimation of the inverse scatter matrix of an elliptically symmetric distribution (Q900790) (← links)
- Improved Stein-type shrinkage estimators for the high-dimensional multivariate normal covariance matrix (Q901577) (← links)
- Shrinkage estimation in the frequency domain of multivariate time series (Q1006672) (← links)
- Shrinkage estimators for large covariance matrices in multivariate real and complex normal distributions under an invariant quadratic loss (Q1036786) (← links)
- Stable estimation of a covariance matrix guided by nuclear norm penalties (Q1623701) (← links)
- Nonparametric Stein-type shrinkage covariance matrix estimators in high-dimensional settings (Q1623798) (← links)
- Estimating large correlation matrices for international migration (Q1624816) (← links)
- Asymptotics for high-dimensional covariance matrices and quadratic forms with applications to the trace functional and shrinkage (Q1639677) (← links)
- Numerical implementation of the QuEST function (Q1658388) (← links)
- Generalized estimating equations with stabilized working correlation structure (Q1658494) (← links)
- Comparison of linear shrinkage estimators of a large covariance matrix in normal and non-normal distributions (Q1659485) (← links)
- Joint regression analysis of mixed-type outcome data via efficient scores (Q1662937) (← links)
- A nonparametric eigenvalue-regularized integrated covariance matrix estimator for asset return data (Q1668581) (← links)
- Using principal component analysis to estimate a high dimensional factor model with high-frequency data (Q1676387) (← links)
- Feature selection for portfolio optimization (Q1699122) (← links)
- Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data (Q1739632) (← links)
- Optimal estimation of a large-dimensional covariance matrix under Stein's loss (Q1750102) (← links)
- A class of optimal estimators for the covariance operator in reproducing kernel Hilbert spaces (Q1755120) (← links)
- Shrinkage for covariance estimation: asymptotics, confidence intervals, bounds and applications in sensor monitoring and finance (Q1757253) (← links)
- Nonlinear GCV and quasi-GCV for shrinkage models (Q1772677) (← links)
- Estimation of two high-dimensional covariance matrices and the spectrum of their ratio (Q1795566) (← links)
- Heterogeneous tail generalized COMFORT modeling via Cholesky decomposition (Q2001089) (← links)
- Weighted covariance matrix estimation (Q2002720) (← links)
- A unified model for regularized and robust portfolio optimization (Q2007869) (← links)
- Subordination methods for free deconvolution (Q2028948) (← links)
- Parameter-free robust optimization for the maximum-Sharpe portfolio problem (Q2030537) (← links)
- A shrinkage approach to joint estimation of multiple covariance matrices (Q2036300) (← links)
- Bootstrap based inference for sparse high-dimensional time series models (Q2040070) (← links)
- High-dimensional linear models: a random matrix perspective (Q2051014) (← links)
- Design-free estimation of integrated covariance matrices for high-frequency data (Q2078572) (← links)
- Copula shrinkage and portfolio allocation in ultra-high dimensions (Q2098001) (← links)
