Matrix Autoregressive Spatio-Temporal Models

DOI10.1080/10618600.2021.1938587OpenAlexW3169266317MaRDI QIDQ5066496

Ruey S. Tsay, Hsin-Cheng Huang, Nan-Jung Hsu

Publication date: 29 March 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10618600.2021.1938587

zbMATH Keywords

dimension reductionmaximum likelihoodmatrix-variate time seriesbilinear autoregressionmulti-resolution spline basis functions

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• FRK

Cites Work

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• Regularized estimation in sparse high-dimensional time series models
• Autoregressive models for matrix-valued time series
• Sparse Bayesian time-varying covariance estimation in many dimensions
• Factor modeling for high-dimensional time series: inference for the number of factors
• Subset selection for vector autoregressive processes using Lasso
• Estimating the dimension of a model
• Factor models for matrix-valued high-dimensional time series
• Fixed Rank Kriging for Very Large Spatial Data Sets
• Classes of Nonseparable, Spatio-Temporal Stationary Covariance Functions
• Constrained Factor Models for High-Dimensional Matrix-Variate Time Series
• High-Dimensional Posterior Consistency in Bayesian Vector Autoregressive Models
• Structured lasso for regression with matrix covariates

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