Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/61237 
Year of Publication: 
1998
Series/Report no.: 
SFB 373 Discussion Paper No. 1998,53
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
A recipe is provided for producing, from a sequence of procedures in the Gaussian regression model, an asymptotically equivalent sequence in the density estimation model with i. i. d. observations. The recipe is, to put it roughly, to calculate square roots of normalised frequencies over certain intervals, add a small random distortion, and pretend these to be observations from a Gaussian discrete regression model.
Subjects: 
asymptotic minimax risk
Nonparametric experiments
deficiency distance
Markov kernel
curve estimation
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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