Data-driven rate-optimal specification testing in regression models
| dc.creator | Guerre, Emmanuel | |
| dc.creator | Lavergne, Pascal | |
| dc.date | 2005-05-30 | |
| dc.date.accessioned | 2026-07-07T08:06:57Z | |
| dc.date.available | 2026-07-07T08:06:57Z | |
| dc.description | We propose new data-driven smooth tests for a parametric regression function. The smoothing parameter is selected through a new criterion that favors a large smoothing parameter under the null hypothesis. The resulting test is adaptive rate-optimal and consistent against Pitman local alternatives approaching the parametric model at a rate arbitrarily close to 1/\sqrtn. Asymptotic critical values come from the standard normal distribution and the bootstrap can be used in small samples. A general formalization allows one to consider a large class of linear smoothing methods, which can be tailored for detection of additive alternatives. | |
| dc.description | Published at http://dx.doi.org/10.1214/009053604000001200 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org) | |
| dc.identifier | https://arxiv.org/abs/math/0505640 | |
| dc.identifier | http://arxiv.org/abs/math/0505640 | |
| dc.identifier | Annals of Statistics 2005, Vol. 33, No. 2, 840-870 | |
| dc.identifier | doi:10.1214/009053604000001200 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/130782 | |
| dc.subject | Statistics Theory | |
| dc.subject | 62G10 (Primary) 62G08. (Secondary) | |
| dc.title | Data-driven rate-optimal specification testing in regression models | |
| dc.type | text |