Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/90545 
Erscheinungsjahr: 
2012
Schriftenreihe/Nr.: 
Discussion Papers No. 131
Verlag: 
Georg-August-Universität Göttingen, Courant Research Centre - Poverty, Equity and Growth (CRC-PEG), Göttingen
Zusammenfassung: 
We present a nonparametric method to decompose a times series into trend, seasonal and remainder components. This fully data-driven technique is based on penalized splines and makes an explicit characterization of the varying seasonality and the correlation in the remainder. The procedure takes advantage of the mixed model representation of penalized splines that allows for the simultaneous estimation of all model parameters from the corresponding likelihood. Simulation studies and three data examples illustrate the effectiveness of the approach.
Schlagwörter: 
Penalized splines
Mixed model
Varying coefficient
Correlated remainder
Dokumentart: 
Working Paper

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