Bandwidth selector for nonparametric recursive density estimation for spatial data defined by stochastic approximation method |
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Authors: | Salim Bouzebda Yousri Slaoui |
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Institution: | 1. LMAC, Université de Technologie de Compiègne, Compiègne, France;2. salim.bouzebda@utc.fr;4. Laboratoire de Mathématiques et Applications, Université de Poitiers, Futuroscope Chasseneuil, France |
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Abstract: | AbstractIn this article we propose an automatic selection of the bandwidth of the recursive kernel density estimators for spatial data defined by the stochastic approximation algorithm. We showed that, using the selected bandwidth and the stepsize which minimize the MWISE (Mean Weighted Integrated Squared Error), the recursive estimator will be quite similar to the nonrecursive one in terms of estimation error and much better in terms of computational costs. In addition, we obtain the central limit theorem for the nonparametric recursive density estimator under some mild conditions. |
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Keywords: | Bandwidth selection density estimation spatial data stochastic approximation algorithm |
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