Rates of convergence in some SLLN under weak dependence conditions
Fazekas and Klesov (2000) found conditions for almost sure convergence rates in the law of large numbers that effectively can be applied if maximal inequalities are available. In the spirit of Móricz (1976), we aim at using those conditions in a weakly dependent framework, and this trick is proved t...
Elmentve itt :
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| Dokumentumtípus: | Cikk |
| Megjelent: |
Bolyai Institute, University of Szeged
Szeged
2010
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| Sorozat: | Acta scientiarum mathematicarum
76 No. 3-4 |
| Kulcsszavak: | Matematika |
| Tárgyszavak: | |
| Online Access: | http://acta.bibl.u-szeged.hu/16371 |
| Tartalmi kivonat: | Fazekas and Klesov (2000) found conditions for almost sure convergence rates in the law of large numbers that effectively can be applied if maximal inequalities are available. In the spirit of Móricz (1976), we aim at using those conditions in a weakly dependent framework, and this trick is proved to be quite efficient, first in the standard law of large numbers and second in the nonparametric estimation context where rates of convergence of the density kernel estimates are also obtained. |
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| Terjedelem/Fizikai jellemzők: | 683-695 |
| ISSN: | 0001-6969 |