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Asymptotic distribution of data-driven smoothers in density and regression estimation under dependence |
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| Authors: | Graciela Boente Ricardo Fraiman |
| Abstract: | We consider automatic data-driven density, regression and autoregression estimates, based on any random bandwidth selector h/T. We show that in a first-order asymptotic approximation they behave as well as the related estimates obtained with the “optimal” bandwidth hT as long as hT/hT → 1 in probability. The results are obtained for dependent observations; some of them are also new for independent observations. |
| Keywords: | Data-driven bandwidth selectors kernel estimates density estimation nonparametric regression autoregression models α -mixing processes Primary 62G05 secondary 62G20 62M10 |