Abstract
Recursive nonparametric density estimation for nonnegative data is considered, using an asymmetric kernel with nonnegative support. It has a computational advantage in a situation where a huge number of data are sequentially collected. The recursive asymmetric kernel estimator keeps desirable asymptotic properties similar to the ordinary non-recursive asymmetric kernel estimator. Also, simulation studies and a real data analysis are performed for illustration.
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