Estimating Linear Dynamical Systems Using Subspace Methods
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Cited by:
- Bauer, Dietmar, 2009. "Estimating ARMAX systems for multivariate time series using the state approach to subspace algorithms," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 397-421, March.
- Christian Kascha, 2012.
"A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models,"
Econometric Reviews, Taylor & Francis Journals, vol. 31(3), pages 297-324.
- Christian Kascha, 2007. "A Comparison of Estimation Methods for Vector Autoregressive Moving-Average Models," Economics Working Papers ECO2007/12, European University Institute.
- Alfredo García-Hiernaux & José Casals & Miguel Jerez, 2012.
"Estimating the system order by subspace methods,"
Computational Statistics, Springer, vol. 27(3), pages 411-425, September.
- García-Hiernaux, Alfredo & Casals, José & Jerez, Miguel, 2007. "Estimating the system order by subspace methods," DES - Working Papers. Statistics and Econometrics. WS ws070301, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Kascha, Christian & Mertens, Karel, 2009.
"Business cycle analysis and VARMA models,"
Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 267-282, February.
- Christian Kascha & Karel Mertens, 2006. "Business Cycle Analysis and VARMA models," Economics Working Papers ECO2006/37, European University Institute.
- Christian Kascha & Karel Mertens, 2008. "Business cycle analysis and VARMA models," Working Paper 2008/05, Norges Bank.
- Dias, Gustavo Fruet & Kapetanios, George, 2018.
"Estimation and forecasting in vector autoregressive moving average models for rich datasets,"
Journal of Econometrics, Elsevier, vol. 202(1), pages 75-91.
- Gustavo Fruet Dias & George Kapetanios, 2014. "Estimation and Forecasting in Vector Autoregressive Moving Average Models for Rich Datasets," CREATES Research Papers 2014-37, Department of Economics and Business Economics, Aarhus University.
- Poskitt, D.S., 2016. "Vector autoregressive moving average identification for macroeconomic modeling: A new methodology," Journal of Econometrics, Elsevier, vol. 192(2), pages 468-484.
- Alfredo García‐Hiernaux, 2011.
"Forecasting linear dynamical systems using subspace methods,"
Journal of Time Series Analysis, Wiley Blackwell, vol. 32(5), pages 462-468, September.
- Alfredo García-Hiernaux, 2009. "Forecasting linear dynamical systems using subspace methods," Documentos de Trabajo del ICAE 2009-02, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
- Arvid Raknerud & Terje Skjerpen & Anders Rygh Swensen, 2010.
"Forecasting key macroeconomic variables from a large number of predictors: a state space approach,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 367-387.
- Arvid Raknerud & Terje Skjerpen & Anders Rygh Swensen, 2007. "Forecasting key macroeconomic variables from a large number of predictors: A state space approach," Discussion Papers 504, Statistics Norway, Research Department.
- Christian Schumacher, 2007.
"Forecasting German GDP using alternative factor models based on large datasets,"
Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 271-302.
- Schumacher, Christian, 2005. "Forecasting German GDP using alternative factor models based on large datasets," Discussion Paper Series 1: Economic Studies 2005,24, Deutsche Bundesbank.
- Bauer, Dietmar & Wagner, Martin, 2009. "Using subspace algorithm cointegration analysis: Simulation performance and application to the term structure," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1954-1973, April.
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