Department of Finance, Copenhagen Business School, Frederiksberg, Denmark.
Department of Mathematics, Aarhus University, Aarhus, Denmark.
J Microsc. 2022 Oct;288(1):40-53. doi: 10.1111/jmi.13141. Epub 2022 Sep 28.
The Cavalieri estimator allows one to infer the volume of an object from area measurements in equidistant planar sections. It is known that applying this estimator in the non-equidistant case may inflate the coefficient of error considerably. We therefore consider a newly introduced variant, the trapezoidal estimator, and make it available to practitioners. Its typical variance behaviour for natural objects is comparable to the equidistant case. We state this unbiased estimator, describe variance estimates and explain how the latter can be simplified under rather general but realistic models for the gaps between sections. Simulations and an application to a synthetic area function based on parietal lobes of 18 monkeys illustrate the new methods.
卡瓦列里估计器允许人们根据等距平面截面的面积测量来推断物体的体积。已知在不等距的情况下应用该估计器可能会大大增加误差系数。因此,我们考虑了一个新引入的变体,即梯形估计器,并将其提供给从业者。它在自然物体上的典型方差行为与等距情况相当。我们提出了这个无偏估计器,描述了方差估计,并解释了在相当一般但现实的截面之间间隙模型下如何简化后者。模拟和对基于 18 只猴子顶叶的合成面积函数的应用说明了新方法。