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Maciej Wilczyński (2003)
Applicationes Mathematicae
Let Y be a random vector taking its values in a measurable space and let z be a vector-valued function defined on that space. We consider gamma minimax estimation of the unknown expected value p of the random vector z(Y). We assume a weighted squared error loss function.
J. Lehn, L. Chen, J. Eichenauer-Herrmann (1990)
Metrika
M. Brockmann, J. Eichenauer-Herrmann (1991)
Applicationes Mathematicae
LanXiang Chen, J. Eichenauer-Herrmann, J. Lehn (1988)
Applicationes Mathematicae
Lanxiang Chen, Heike Hofmann, Jürgen Eichenauer-Herrmann, Jürgen Kindler (1991)
Lucien Birgé, Pascal Massart (2001)
Journal of the European Mathematical Society
Our purpose in this paper is to provide a general approach to model selection via penalization for Gaussian regression and to develop our point of view about this subject. The advantage and importance of model selection come from the fact that it provides a suitable approach to many different types of problems, starting from model selection per se (among a family of parametric models, which one is more suitable for the data at hand), which includes for instance variable selection in regression models,...
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