A Modelling Approach for Bandwidth Selection in Kernel Density Estimation
A Modelling Approach for Bandwidth Selection in Kernel Density Estimation
复制标题
核密度估计中带宽选择的建模方法
DOI：
10.1007/978-3-662-01131-7_22
复制
发表时间：
1998
影响因子：
0.6
通讯作者：
M. Brewer
中科院分区：
文献类型：
--
作者：
M. Brewer
提出了一种单变量核密度估计中带宽选择的新方法。我们不是专注于最小化一些基于平均积分平方误差(MISE)的标准，而是为数据建立模型，并使用抽样方法来推断带宽，而MISE直接取决于(未知的)真实密度。该模型是贝叶斯模型，值得注意的是，它允许对密度估计的平滑程度的主观变化进行系统调整。
A new procedure is proposed for bandwidth selection in univariate kernel density estimation. Rather than concentrate on minimising some criterion based upon the mean integrated square error (MISE), which depends directly on the (unknown) true density, we build a model for the data and use sampling methods to make inferences about the bandwidths. The model is Bayesian, and it is noted that it allows for systematic adjustment for subjective changes in smoothness of the density estimate.