Extracting a low-dimensional predictable time series
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Publication:2147946
DOI10.1007/s11081-021-09643-xOpenAlexW3170494524MaRDI QIDQ2147946
S. Joe Qin, Yining Dong, Stephen P. Boyd
Publication date: 20 June 2022
Published in: Optimization and Engineering (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11081-021-09643-x
Inference from stochastic processes (62Mxx) Multivariate analysis (62Hxx) Stochastic systems and control (93Exx)
Cites Work
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- AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM
- Factor modeling for high-dimensional time series: inference for the number of factors
- Optimization on a Grassmann manifold with application to system identification
- Design of measurement difference autocovariance method for estimation of process and measurement noise covariances
- Graph-based predictable feature analysis
- Subspace algorithms for the stochastic identification problem
- High-dimensional VAR with low-rank transition
- Blind Source Separation Using Temporal Predictability
- Estimation of latent factors for high-dimensional time series
- Modelling multiple time series via common factors
- Reduced rank models for multiple time series
- Identifying a Simplifying Structure in Time Series
- On- and off-line identification of linear state-space models
- Nested Reduced-Rank Autogressive Models for Multiple Time Series
- A canonical analysis of multiple time series
- The Geometry of Algorithms with Orthogonality Constraints
- Slow Feature Analysis: Unsupervised Learning of Invariances
- Low Rank and Structured Modeling of High-Dimensional Vector Autoregressions
- Some results on multivariate autoregressive index models
- System Identification of High-Dimensional Linear Dynamical Systems With Serially Correlated Output Noise Components
- Forecasting Multiple Time Series With One-Sided Dynamic Principal Components
- EFFICIENT ESTIMATION OF FACTOR MODELS