Niveau: Supérieur, Doctorat, Bac+8
Nonparametric regression estimation for random fields in a fixed-design Mohamed EL MACHKOURI 24th January 2005 Abstract We investigate the nonparametric estimation for regression in a fixed-design setting when the errors are given by a field of dependent random variables. Sufficient conditions for kernel estimators to con- verge uniformly are obtained. These estimators can attain the optimal rates of uniform convergence and the results apply to a large class of random fields which contains martingale-difference random fields and mixing random fields. AMS Subject Classifications (2000): 60G60, 62G08 Key words and phrases: nonparametric regression estimation, kernel estimators, strong consistency, fixed-design, exponential inequalities, martingale difference random fields, mixing, Orlicz spaces. Short title: Nonparametric regression in a fixed design.
- spatial pro
- real random variable
- investigate uniform
- nonparametric regression
- uniform mixing
- mixing coefficient
- ?? defined
- random fields