A robust-filtering method for noisy non-stationary multivariate time series with econometric applications

DOI10.1007/s42081-020-00102-yzbMath1477.62261OpenAlexW3119178728MaRDI QIDQ825334

Seisho Sato, Naoto Kunitomo

Publication date: 17 December 2021

Published in: Japanese Journal of Statistics and Data Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42081-020-00102-y

zbMATH Keywords

trend-cycleSIMLerrors-variables modelsFourier-inversionmacro-economic data in JapanMüller-Watson methodnoisy non-stationary time seriesreal-valued orthogonal processrobust-filteringseasonality and noise

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (1)

Detecting factors of quadratic variation in the presence of market microstructure noise

Cites Work

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