基于频率统计和贝叶斯统计的零事件率区间估计方法比较研究

目的零事件率是当抽样事件数为零时二项率的一种特殊情形,对其区间估计缺乏深入研究。方法利用二项分布和贝塔分布的关系,使用SAS 9.8设计三层嵌套9.4亿个参数空间点的计算密集型模拟实验,从区间精度、准确度和基于精确法的相对误差三个方面比较了三种频率方法和两种贝叶斯方法区间估计的统计性能,并通过医学实例说明其应用。结果首次报告了在保证覆盖率满足名义水平的条件下,精确法优于Wilson近似法的临界样本量。在平衡估计精度(区间宽度)和估计准确度(覆盖率)的思想指导下,通过大规模统计模拟和实例分析,推荐使用精确法进行零事件率的区间估计。结论随着医学技术的进步,零事件率越来越多地出现在医学研究中,在对这一特殊率进行统计推断时,推荐使用精确法。

Multi-source data-based 3D digital preservation of large scale ancient chinese architecture:A case report

The 3D digitalization and documentation of ancient Chinese architecture is challenging because of architectural complexity and structural delicacy.To generate complete and detailed models of this architecture,it is better to acquire,process,and fuse multi-source data instead of single-source data.In this paper,we describe our work on 3D digital preservation of ancient Chinese architecture based on multi source data.We first briefly introduce two surveyed ancient Chinese temples,Foguang Temple and Nanchan Temple.Then,we report the data acquisition equipment we used and the multi-source data we acquired.Finally,we provide an overview of several applications we conducted based on the acquired data,including ground and aerial image fusion,image and LiDAR(light detection and ranging)data fusion,and architectural scene surface reconstruction and semantic modeling.We believe that it is necessary to involve multi-source data for the 3D digital preservation of ancient Chinese architecture,and that the work in this paper will serve as a heuristic guideline for the related research communities.

贝叶斯层次模型的群组变异参数先验设置探讨

目的本研究旨在探讨不同先验分布对贝叶斯层次模型关键参数估计的影响,并分析群组水平数量变化对估计精度的作用。方法通过案例分析和模拟研究对模型中群组变异参数分别赋予逆伽马分布、半柯西分布和指数分布,比较其性能及受群组水平数量变化的影响。结果指数分布由于尾部较短,可能低估方差;而逆伽马和半柯西分布因为尾部较厚,能提供更为稳健的估计。在群组水平较多的情况下,模型对变异的估计更加精确,而随着群组数量的减少,估计误差会增大。结论在小样本条件下,半柯西和指数分布因其便于结合外部信息且能够合理反映变异参数的变化特征,成为更适当的选择。这些发现为贝叶斯层次模型在实际应用中选择群组变异参数的先验提供了重要参考依据。