Converges in of nearest neighbor regression function estimate for strong mixing processes
Abstract
In this paper, we will study the issue of estimating regression function using k-nearest neighbors method (knn) for mixing processes. We will extend the convergence in for knn regression from independent case to the dependent case; In addition, we will conduct a simulation study using R software program to display the importance and influence of choosing number of neighbors (k) and the sample size (n) on behavior of the estimator. For this purpose, the mean squares error criterion (MSE) was used. The high variability of the MSE results shows that knn estimators are very sensitive to the choice of the number of neighbors. More results show that the higher value of n, the more accurate and effective the estimator.
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