Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence
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 probabi...
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1995
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03195724_v23_n4_p383_Boente http://hdl.handle.net/20.500.12110/paper_03195724_v23_n4_p383_Boente |
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paper:paper_03195724_v23_n4_p383_Boente2023-06-08T15:31:58Z Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence 62M10. autoregression models Data‐driven bandwidth selectors density estimation kernel estimates nonparametric regression Primary 62G05 secondary 62G20 α‐mixing processes 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. Copyright © 1995 Statistical Society of Canada 1995 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03195724_v23_n4_p383_Boente http://hdl.handle.net/20.500.12110/paper_03195724_v23_n4_p383_Boente |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
62M10. autoregression models Data‐driven bandwidth selectors density estimation kernel estimates nonparametric regression Primary 62G05 secondary 62G20 α‐mixing processes |
| spellingShingle |
62M10. autoregression models Data‐driven bandwidth selectors density estimation kernel estimates nonparametric regression Primary 62G05 secondary 62G20 α‐mixing processes Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence |
| topic_facet |
62M10. autoregression models Data‐driven bandwidth selectors density estimation kernel estimates nonparametric regression Primary 62G05 secondary 62G20 α‐mixing processes |
| description |
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. Copyright © 1995 Statistical Society of Canada |
| title |
Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence |
| title_short |
Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence |
| title_full |
Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence |
| title_fullStr |
Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence |
| title_full_unstemmed |
Asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence |
| title_sort |
asymptotic distribution of data‐driven smoothers in density and regression estimation under dependence |
| publishDate |
1995 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03195724_v23_n4_p383_Boente http://hdl.handle.net/20.500.12110/paper_03195724_v23_n4_p383_Boente |
| _version_ |
1768541655116283904 |