Using Richardson Extrapolation to Improve the Accuracy of Processing and Analyzing Empirical Data

被引：0
|
作者：
O. A. Popova
机构：
[1] Siberian Federal University,
来源：
Measurement Techniques | 2019年 / 62卷
关键词：
kernel estimates; accuracy improvement; Richardson extrapolation; Runge rule; estimates of the derivatives of probability density functions;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We investigate properties of empirical data under random uncertainty. A new approach is proposed to improve the accuracy of constructing a probability density function and estimating its error. The method uses Richardson extrapolation and Runge rules for kernel estimates with various smoothing options. It is shown that the application of the Runge rules enables evaluating the error of kernel estimates for a probability density function and the value of its second derivative.
引用
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页码：111 / 117
页数：6
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