Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/66264 
Year of Publication: 
1997
Series/Report no.: 
SFB 373 Discussion Paper No. 1997,100
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
The problem of estimation of the finite dimensional parameter in a partial linear model is considered. We derive upper and lower bounds for the second minimax order risk and show that the second order minimax estimator is a penalized maximum likelihood estimator. It is well known that the performance of the estimator is depending on the choice of a smoothing parameter. We propose a practically feasible adaptive procedure for the penalization choice.
Subjects: 
second order minimax risk
Adaptive estimation
penalized likelihood
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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