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l 1 - penalized likelihood smoothing of volatility processes allowing for abrupt changes
Neto, David; Sardy, Sylvain; Tseng, Paul - 2009
Persistent link: https://www.econbiz.de/10003926975
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Using wavelets for time series forecasting : does it pay off?
Schlüter, Stephan; Deuschle, Carola - 2010
By means of wavelet transform a time series can be decomposed into a time dependent sum of frequency components. As a result we are able to capture seasonalities with time-varying period and intensity, which nourishes the belief that incorporating the wavelet transform in existing forecasting...
Persistent link: https://www.econbiz.de/10003966651
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Time varying dimension models
Chan, Joshua C. C.; Koop, Gary; Leon-Gonzalez, Roberto; … - 2010
Persistent link: https://www.econbiz.de/10008657953
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When long memory meets the Kalman Filter : a comparative study
Grassi, Stefano; Santucci de Magistris, Paolo - 2011
Persistent link: https://www.econbiz.de/10009006828
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Time series analysis by state space methods
Durbin, James; Koopman, Siem Jan - 2012 - Second edition
Persistent link: https://www.econbiz.de/10009570767
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A note on particle filters applied to DSGE models
Fasolo, Angelo Marsiglia - 2012
Persistent link: https://www.econbiz.de/10009573931
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A nonparametric method for asymmetrically extending signal extraction filters
McElroy, Tucker - In: Journal of forecasting 30 (2011) 7, pp. 597-621
Persistent link: https://www.econbiz.de/10009380004
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A novel wavelet based approach for time series data analysis
Meinl, Thomas - 2011
Persistent link: https://www.econbiz.de/10009152702
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Parameter space restrictions in state space models
Jun, Duk Bin; Kim, Dong Soo; Park, Sungho; Park, Myoung Hwan - In: Journal of forecasting 31 (2012) 2, pp. 109-123
Persistent link: https://www.econbiz.de/10009503691
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A time-varying parameter model of inflation in India
Kumar, Sudhanshu; Srinivasan, Naveen; Ramachandran, Muthiah - In: Indian growth and development review 5 (2012) 1, pp. 25-50
Persistent link: https://www.econbiz.de/10009551661