Deconvolution of supersmooth densities with smooth noise
By Cristina Butucea. 2004
76 citations recorded by the source corpus.
Subfields: Finance, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/84012adf6ee185e6bb96e41c230caf6a11e1878d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
- Claire Lacour
- Peter Hall
- Soumendra Nath Lahiri
- Stéphane Girard
- Laurent Gardes
- A. C. Davison
- Jonathan A. Tawn
- Jan Beirlant
In Management Science and Operations Research
In Statistics and Probability
- Soumendra Nath Lahiri
- Claire Lacour
- Peter Hall
- H. Muller
- Aurore Delaigle
- Han Lin Shang
- Jing Lei
- Peter Buhlmann
Citations in the corpus
- Rates of convergence for nonparametric deconvolution (2006, background): “En premier [9] et plus r´ecemment [ 1 ], [2] et [4] ont ´etudi´e des estimateurs dans ce contexte.”
- Estimation of distributions, moments and quantiles in deconvolution problems (2008, background): “Recent contributions to optimality theory, in the context of density estimation, include those of Butucea (2004), who gave minimax convergence rates in cases where the unknown density belongs to a class of supersmooth functions, and the error distribution is ordinary-smooth; and Butucea and…”
- Adaptive estimation of linear functionals in the convolution model and applications (2009, unknown): “We shall denote by φn the minimax rate of convergence over the class S(λ); see, for example, Butucea [4] for a definition.”