Conditioning theory of the equality constrained quadratic programming and its applications
DOI10.1080/03081087.2019.1623858zbMath1467.65037OpenAlexW2948016889WikidataQ114849554 ScholiaQ114849554MaRDI QIDQ5858718
Publication date: 14 April 2021
Published in: Linear and Multilinear Algebra (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03081087.2019.1623858
condition numberportfolio selectioncovariance matrix estimatorequality constrained quadratic programmingfirst-order perturbation bound
Norms of matrices, numerical range, applications of functional analysis to matrix theory (15A60) Numerical computation of matrix norms, conditioning, scaling (65F35) Conditioning of matrices (15A12)
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- A well-conditioned estimator for large-dimensional covariance matrices
- Sensitivity analysis and calibration of the covariance matrix for stable portfolio selection
- A contribution to the theory of condition
- Algebraic properties of the rank-deficient equality-constrained and weighted least squares problems
- Perturbation bounds for constrained and weighted least squares problems
- A note on the condition number of the scaled total least squares problem
- Mixed and componentwise condition numbers for a linear function of the solution of the total least squares problem
- On the partial condition numbers for the indefinite least squares problem
- Partial condition number for the equality constrained linear least squares problem
- On the condition number of linear least squares problems in a weighted Frobenius norm
- Small sample statistical condition estimation for the total least squares problem
- Probabilistic upper bounds for the matrix two-norm
- Restoring Definiteness via Shrinking, with an Application to Correlation Matrices with a Fixed Block
- Condition
- Mixed, Componentwise, and Structured Condition Numbers
- Sensitivity Analysis for Mean-Variance Portfolio Problems
- On mixed and componentwise condition numbers for Moore–Penrose inverse and linear least squares problems
- Numerical Optimization
- Small-Sample Statistical Condition Estimates for General Matrix Functions
- A Subspace Error Estimate for Linear Systems
- A condition analysis of the weighted linear least squares problem using dual norms
- Accuracy and Stability of Numerical Algorithms
- Positive-Definite ℓ1-Penalized Estimation of Large Covariance Matrices
- Vast Portfolio Selection With Gross-Exposure Constraints
- The effect of L1 penalization on condition number constrained estimation of precision matrix
- A Theory of Condition
- Condition-Number-Regularized Covariance Estimation
- On condition numbers for the canonical generalized polar decompostion of real matrices
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