Piecewise linear density estimation for sampled data
| dc.creator | Lejeune, François-Xavier | |
| dc.date | 2007-09-28 | |
| dc.date | 2009-01-17 | |
| dc.date.accessioned | 2026-07-07T12:30:50Z | |
| dc.date.available | 2026-07-07T12:30:50Z | |
| dc.description | Nonparametric density estimation is considered for a discretely observed stationary continuous-time process. For each of three given time sampling procedures either random or deterministic, we establish that histograms and frequency polygons can reach the same optimal $L_{2}$-rates as in the independent and identically distributed case. Moreover, thanks to a suitable "high frequency" sampling design, these rates are derived together with a minimized time of observation depending on the regularity of sample paths. | |
| dc.description | 23 pages | |
| dc.identifier | https://arxiv.org/abs/0709.4543 | |
| dc.identifier | http://arxiv.org/abs/0709.4543 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/216254 | |
| dc.subject | Statistics Theory | |
| dc.subject | 62G07, 62M | |
| dc.title | Piecewise linear density estimation for sampled data | |
| dc.type | text |