Dynamic principal component analysis with missing values

DOI10.1080/02664763.2019.1699910OpenAlexW2992324966MaRDI QIDQ5861402

Junhyeon Kwon, Yaeji Lim, Hee-Seok Oh

Publication date: 1 March 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2019.1699910

zbMATH Keywords

dynamic factor modelspectral density matrixdynamic principal component analysisfrequency domain principal component analysismissing problem

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• freqdom.fda

Cites Work

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• A two-step estimator for large approximate dynamic factor models based on Kalman filtering
• Maximum likelihood estimation for dynamic factor models with missing data
• Fitting dynamic factor models to non-stationary time series
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Forecasting Using Principal Components From a Large Number of Predictors
• Detecting Common Signals in Multiple Time Series Using the Spectral Envelope
• Dynamic Functional Principal Components
• Inferential Theory for Factor Models of Large Dimensions
• Determining the Number of Factors in Approximate Factor Models

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