A robust-filtering method for noisy non-stationary multivariate time series with econometric applications
type: Item
instance of: scholarly article
title: A robust-filtering method for noisy non-stationary multivariate time series with econometric applications
zbMATH Open document ID: 1477.62261
author: Naoto Kunitomo
author: Seisho Sato
published in: Japanese Journal of Statistics and Data Science
publication date: 2021-12-17T00:00:00Z
Mathematics Subject Classification ID: 62M20
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62P20
zbMATH DE Number: 7447486
zbMATH Keywords: noisy non-stationary time series
zbMATH Keywords: errors-variables models
zbMATH Keywords: trend-cycle
zbMATH Keywords: seasonality and noise
zbMATH Keywords: robust-filtering
zbMATH Keywords: SIML
zbMATH Keywords: Fourier-inversion
zbMATH Keywords: real-valued orthogonal process
zbMATH Keywords: Müller-Watson method
zbMATH Keywords: macro-economic data in Japan
MaRDI profile type: Publication
full work available at URL: s42081-020-00102-y
OpenAlex ID: W3119178728
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DOI: 10.1007/S42081-020-00102-Y
description: scientific article; zbMATH DE number 7447486