Robust kernel estimators for additive models with dependent observations
Robust nonparametric estimators for additive regression or autoregression models under an α-mixing condition are proposed. They are based on local M-estimators or local medians with kernel weights, and their asymptotic behaviour is studied. Moreover, these local M-estimators achieve the same univari...
Guardado en:
| Autores principales: | , |
|---|---|
| Formato: | JOUR |
| Materias: | |
| Acceso en línea: | http://hdl.handle.net/20.500.12110/paper_03195724_v26_n2_p239_Bianco |
| Aporte de: |
| Sumario: | Robust nonparametric estimators for additive regression or autoregression models under an α-mixing condition are proposed. They are based on local M-estimators or local medians with kernel weights, and their asymptotic behaviour is studied. Moreover, these local M-estimators achieve the same univariate rate of convergence as their linear relatives. |
|---|