Forecasting Multiple Time Series With One-Sided Dynamic Principal Components

DOI10.1080/01621459.2018.1520117zbMath1428.62401arXiv1708.04705OpenAlexW2963724581MaRDI QIDQ5208073

Ezequiel Smucler, Víctor J. Yohai, Daniel Peña

Publication date: 15 January 2020

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1708.04705

zbMATH Keywords

dimensionality reductiondynamic factor modelshigh-dimensional time series

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (3)

Extracting a low-dimensional predictable time series ⋮ Data science, big data and statistics ⋮ Consistency of generalized dynamic principal components in dynamic factor models

Uses Software

• forecast
• Forecast

Cites Work

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• Statistics for high-dimensional data. Methods, theory and applications.
• High breakdown-point and high efficiency robust estimates for regression
• Robust and sparse estimators for linear regression models
• Dynamic factor models with infinite-dimensional factor spaces: one-sided representations
• Coordinate descent algorithms
• Dynamic factor models with infinite-dimensional factor space: asymptotic analysis
• Forecasting with nonstationary dynamic factor models
• Factor models in high-dimensional time series: A time-domain approach
• Identifying a Simplifying Structure in Time Series
• Nested Reduced-Rank Autogressive Models for Multiple Time Series
• A canonical analysis of multiple time series
• Forecasting Using Principal Components From a Large Number of Predictors
• Determining the Number of Factors in the General Dynamic Factor Model
• OPENING THE BLACK BOX: STRUCTURAL FACTOR MODELS WITH LARGE CROSS SECTIONS
• Determining the Number of Factors in Approximate Factor Models
• Large Covariance Estimation by Thresholding Principal Orthogonal Complements
• The Generalized Dynamic Factor Model

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