Renormalizing Upper and Lower Bounds for Integrated Risk in the White Noise Model:
Low, Mark G.
Ann. Statist., Tome 21 (1993) no. 1, p. 577-589 / Harvested from Project Euclid
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Renormalization arguments are used to derive optimal rates of convergence, under integrated squared error loss, for parameter spaces having a certain rectangular structure.
Publié le : 1993-06-14
Classification:  Nonparametric functional estimation,  renormalization,  white noise model,  62G07,  62C20 
@article{1176349137,
     author = {Low, Mark G.},
     title = {Renormalizing Upper and Lower Bounds for Integrated Risk in the White Noise Model:},
     journal = {Ann. Statist.},
     volume = {21},
     number = {1},
     year = {1993},
     pages = { 577-589},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176349137}
}

Low, Mark G. Renormalizing Upper and Lower Bounds for Integrated Risk in the White Noise Model:. Ann. Statist., Tome 21 (1993) no. 1, pp.  577-589. http://gdmltest.u-ga.fr/item/1176349137/