Abstract

In this paper, we study the asymptotic distribution of the plug-in kernel density estimator of the Matusita's overlapping measure. By utilizing the convergence of functional of stochastic processes, we show, under certain conditions, that the asymptotic distribution of the plug-in kernel density estimator (KDE) of Matusita's overlapping measure is normal distribution. Also, a small simulation study is conducted to support the theoretical finding of this paper. Furthermore, we apply our finding to a breast cancer data.

中文翻译：

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Matusita重叠测度的渐近分布

摘要

在本文中，我们研究了Matusita重叠测度的插件核密度估计器的渐近分布。通过利用随机过程的收敛性，我们证明了在一定条件下，Matusita重叠测度的插入核密度估计器（KDE）的渐近分布是正态分布。此外，进行了一次小型模拟研究以支持本文的理论发现。此外，我们将我们的发现应用于乳腺癌数据。