Adaptive estimation of the conditional intensity of marker-dependent counting processes
| dc.creator | Comte, F. | |
| dc.creator | Gaïffas, S. | |
| dc.creator | Guilloux, A. | |
| dc.date | 2008-10-23 | |
| dc.date.accessioned | 2026-07-07T10:12:42Z | |
| dc.date.available | 2026-07-07T10:12:42Z | |
| dc.description | We propose in this work an original estimator of the conditional intensity of a marker-dependent counting process, that is, a counting process with covariates. We use model selection methods and provide a non asymptotic bound for the risk of our estimator on a compact set. We show that our estimator reaches automatically a convergence rate over a functional class with a given (unknown) anisotropic regularity. Then, we prove a lower bound which establishes that this rate is optimal. Lastly, we provide a short illustration of the way the estimator works in the context of conditional hazard estimation. | |
| dc.description | 31 pages, 3 figures | |
| dc.identifier | https://arxiv.org/abs/0810.4263 | |
| dc.identifier | http://arxiv.org/abs/0810.4263 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/172269 | |
| dc.subject | Statistics Theory | |
| dc.subject | 62N02; 62G05 | |
| dc.title | Adaptive estimation of the conditional intensity of marker-dependent counting processes | |
| dc.type | text |