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.

中文翻译：

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非负数据的递归非对称核密度估计

考虑使用非负支持的非对称内核对非负数据进行递归非参数密度估计。在顺序收集大量数据的情况下，它具有计算优势。递归非对称核估计器保持了与普通非递归非对称核估计器相似的理想渐近特性。此外，还进行了模拟研究和实际数据分析以进行说明。