A ridge-parameter approach to deconvolution
Kernel methods for deconvolution have attractive features, and prevail in the literature. However, they have disadvantages, which include the fact that they are usually suitable only for cases where the error distribution is infinitely supported and its characteristic function does not ever vanish. Even in these settings, optimal convergence rates are achieved by kernel estimators only when the kernel is chosen to adapt to the unknown smoothness of the target distribution. In this paper...[Show more]
|Collections||ANU Research Publications|
|Source:||Annals of Statistics|
|01_Peter Hal_A_ridge-parameter_approach_to_2007.pdf||Published Version||357.1 kB||Adobe PDF|
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