Empirical-likelihood-based confidence interval for the mean with a heavy-tailed distribution
| dc.creator | Peng, Liang | |
| dc.date | 2004-06-25 | |
| dc.date.accessioned | 2026-07-07T08:06:24Z | |
| dc.date.available | 2026-07-07T08:06:24Z | |
| dc.description | Empirical-likelihood-based confidence intervals for a mean were introduced by Owen [Biometrika 75 (1988) 237-249], where at least a finite second moment is required. This excludes some important distributions, for example, those in the domain of attraction of a stable law with index between 1 and 2. In this article we use a method similar to Qin and Wong [Scand. J. Statist. 23 (1996) 209-219] to derive an empirical-likelihood-based confidence interval for the mean when the underlying distribution has heavy tails. Our method can easily be extended to obtain a confidence interval for any order of moment of a heavy-tailed distribution. | |
| dc.identifier | https://arxiv.org/abs/math/0406523 | |
| dc.identifier | http://arxiv.org/abs/math/0406523 | |
| dc.identifier | Annals of Statistics 2004, Vol. 32, No. 3, 1192-1214 | |
| dc.identifier | doi:10.1214/009053604000000328 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/130592 | |
| dc.subject | Statistics Theory | |
| dc.subject | 62G15 (Primary) 62G30 (Secondary) | |
| dc.title | Empirical-likelihood-based confidence interval for the mean with a heavy-tailed distribution | |
| dc.type | text |