Optimal smoothing in adaptive location estimation
In this paper, we consider higher order performance of kernel based adaptive location estimates. We show how much one loses in efficiency without knowing the underlying translation density, and derive the optimal order of the bandwidths involved in kernel estimation of the efficient score function....
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
1997
|
| In: |
Journal of statistical planning and inference
Year: 1997, Jahrgang: 58, Heft: 2, Pages: 333-348 |
| ISSN: | 0378-3758 |
| DOI: | 10.1016/S0378-3758(96)00085-7 |
| Online-Zugang: | Verlag, Volltext: http://dx.doi.org/10.1016/S0378-3758(96)00085-7 Verlag, Volltext: http://www.sciencedirect.com/science/article/pii/S0378375896000857 
|
| Verfasserangaben: | Enno Mammen, Byeong U. Park |
| Zusammenfassung: | In this paper, we consider higher order performance of kernel based adaptive location estimates. We show how much one loses in efficiency without knowing the underlying translation density, and derive the optimal order of the bandwidths involved in kernel estimation of the efficient score function. The optimal order is obtained by minimizing the loss of efficiency in terms of estimating the location parameter. The main lesson here is that the optimal order of the bandwidths are different from those for optimal estimation of the score function. This implies that optimal estimation of the score function does not lead to second order optimal location estimation. |
|---|---|
| Beschreibung: | Available online: 12 May 1998 Gesehen am 19.02.2018 |
| Beschreibung: | Online Resource |
| ISSN: | 0378-3758 |
| DOI: | 10.1016/S0378-3758(96)00085-7 |