[Statlist] Séminaires de Statistique - Institut de Statistique, Université de Neuchâtel

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Séminaire de Statistique 
Institut de Statistique, Université de Neuchâtel 

Pierre à Mazel 7 (1er étage,salle 110), Neuchâtel,

http://www2.unine.ch/statistics

Mardi 24 avril 2007, 11h00

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Yuedong Wang, Department of Statistics and Applied Probability, University of California, Santa Barbara, USA

 

Spline Smoothing with Correlated Random Errors 


Abstract. Spline smoothing techniques are commonly used to estimate the mean function in a nonparametric regression model. Their performances depend greatly on the choice of smoothing parameters. Many methods of selecting smoothing parameters such as GML, GCV and UBR have been developed under the assumption of independent observations. They tend to underestimate smoothing parameters when data are correlated. 


We assume that observations are correlated and that the correlation matrix depends on a parsimonious set of parameters. We extend the GML, GCV and UBR methods to estimate the smoothing parameters and the correlation parameters simultaneously. 


 


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