On two methods to evaluate the uncertainty of derivatives calculated from polynomials fitted to experimental data
On two methods to evaluate the uncertainty of derivatives calculated from polynomials fitted to experimental data
复制标题
DOI：
10.1088/0026-1394/42/1/005
复制
发表时间：
2005-02-01
期刊：
影响因子：
2.4
通讯作者：
Roth, P
中科院分区：
文献类型：
--
作者：
Cordero, RR;Roth, P
我们比较了两个程序的性能用于评估的不确定性计算的衍生物从多项式拟合实验数据。这些程序符合国际建议，并且独立于用于获得数据的实验技术，它们是有效的。第一个过程涉及在不确定性下执行最小二乘多项式平差。第二个过程是基于蒙特卡罗技术。两者都是计算机辅助的。作为一个例子，我们评估了与拟合到实验数据的表面的梯度相关的标准不确定度，这些实验数据形成了三维空间中的一组点。我们发现，这两种方法呈现非常相似的结果。
We compare the performance of two procedures used for the evaluation of uncertainty of derivatives computed from a polynomial fitted to experimental data. These procedures agree with international recommendations and they are valid independently of the experimental technique used to obtain the data. The first procedure involves performing a least-squares polynomial adjustment under uncertainty. The second procedure is based on Monte Carlo techniques. Both are computer-assisted. As an example, we evaluated the standard uncertainty associated with the gradient of a surface fitted to experimental data that formed a set of points in a three-dimensional space. We found that both methods render very similar results.