On Random-design Model with Dependent Errors
نویسندگان
چکیده
We consider random-design nonparametric regression model in which errors depend on predictors as well as on unobservable latent variables. Predictors and latent variables may be shortor long-range dependent. In this setup asymptotic distributions of the Nadaraya-Watson estimate of regression function are studied under various conditions. We prove that their form depends on three factors: amount of smoothing and strength of dependence of both predictors and latent variables. Our results go beyond earlier ones by allowing more general dependence structure.
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