High-dimensional dynamic systems identification with additional constraints
From MaRDI portal
Publication:5093707
DOI10.1080/03610926.2020.1836219OpenAlexW3103586086MaRDI QIDQ5093707
Publication date: 1 August 2022
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1912.09767
system identificationVARX modelnuclear-norm minimizationhigh-dimensional statistical inferencelow-rank recovery
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Bayesian Multivariate Time Series Methods for Empirical Macroeconomics
- Regularized estimation in sparse high-dimensional time series models
- Simple bounds for recovering low-complexity models
- Statistics for high-dimensional data. Methods, theory and applications.
- Estimation of (near) low-rank matrices with noise and high-dimensional scaling
- Optimal selection of reduced rank estimators of high-dimensional matrices
- Convex optimization methods for dimension reduction and coefficient estimation in multivariate linear regression
- Uniform uncertainty principle for Bernoulli and subgaussian ensembles
- On the rank minimization problem and its control applications
- Characterization of the subdifferential of some matrix norms
- On the sample complexity of the linear quadratic regulator
- Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
- High-Dimensional Statistics
- Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)
- High-Dimensional Posterior Consistency in Bayesian Vector Autoregressive Models
- Tight Oracle Inequalities for Low-Rank Matrix Recovery From a Minimal Number of Noisy Random Measurements
- Recovering Low-Rank Matrices From Few Coefficients in Any Basis
- A unified framework for high-dimensional analysis of \(M\)-estimators with decomposable regularizers
This page was built for publication: High-dimensional dynamic systems identification with additional constraints
