A bandwidth selection for kernel density estimation of functions of random variables
A bandwidth selection for kernel density estimation of functions of random variables
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DOI：
10.1016/j.csda.2003.10.013
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发表时间：
2004-08-01
影响因子：
1.8
通讯作者：
Ahmad, IA
中科院分区：
文献类型：
--
作者：
Mugdadi, AR;Ahmad, IA
本文研究了m个独立同分布随机变量函数g(X-1，X-2，…，X-m)的概率密度函数的估计问题。在核密度估计中，带宽的选择是非常重要的。在m=1且g是恒等式的情况下，在核平滑方法中选择带宽的几种方法是已知的。在这项研究中，我们将使用最小二乘交叉验证和对比的方法来推导带宽。我们将使用蒙特卡罗模拟和现实生活中的一个例子对这两种方法进行比较。(C)2003爱思唯尔B.V.保留所有权利。
In this investigation, the problem of estimating the probability density function of a function of m independent identically distributed random variables, g(X-1,X-2,...,X-m) is considered. The choice of the bandwidth in the kernel density estimation is very important. Several approaches are known for the choice of bandwidth in the kernel smoothing methods for the case m = 1 and g is the identity. In this study we will derive the bandwidth using the least square cross validation and the contrast methods. We will compare between the two methods using Monte Carlo simulation and using an example from the real life. (C) 2003 Elsevier B.V. All rights reserved.