Local M - Estimation of Regression Function
نویسنده
چکیده
In this article, we investigate a robust version of local linear regression smoothers for stationary and censored stochastic processes by using M-type local polynomial techniques and transformations. Under some regularity conditions, we establish the weak and strong consistency as well as the asymptotic normality of proposed estimators. We propose an easily implemented bandwidth selection criterion based on the modiied multifold cross-validation, and a consistent estimator of the asymptotic covariance is also proposed.
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