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本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。

DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要;缺少可靠材料时保留待补状态。

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分类依据与纠错

AI 根据所提供的论文材料归类:摘要核心是散射实验的局部拟合与窗口选择,自回归误差本身不足以确定宏观时间序列分类。

反馈分类问题

正在核对关联版本…

代码、数据与补充材料

正在核对对应版本的资源…

关注这篇论文的作者
Cody Alsaker
F. Jay Breidt

小角 X 射线散射实验中回转半径的最小均方误差估计

研究问题
利用小角 X 射线散射数据估计分子回转半径时,如何选择低散射角窗口,并兼顾估计误差、方差及重复实验可比性?
方法与思路
作者采用带自回归误差的局部多项式模型,建立窗口选择、最小均方误差估计及方差估计方法和相应渐近理论。
材料陈述的贡献
摘要称模拟支持渐近近似及相对既有标准方法的改进;半自动流程支持重复估计,并展示对多个强度曲线的后续分析。
阅读关注点
核对局部近似与自回归误差设定、最优窗口所依据的误差准则,以及重复实验设计和后续分析如何处理估计不确定性。
阅读边界
依据版本未注明的 OpenAlex 索引摘要;最优窗口条件、方差公式和比较细节未展开,不能推断不同实验条件下的优势。

原文摘要

Small-angle X-ray scattering (SAXS) is a technique that yields low-resolution structural information of biological macromolecules by exposing a large ensemble of molecules in solution to a powerful X-ray beam. The beam interacts with the molecules and the intensity of the scattered beam is recorded on a detector plate. The radius of gyration for a molecule, which is a measure of the spread of its mass, can be estimated from the lowest scattering angles of SAXS data. This estimation method requires specification of a window of scattering angles. Under a local polynomial model with autoregressive errors, we develop methodology and supporting asymptotic theory for selection of an optimal window, minimum mean square error estimation of the radius of gyration, and estimation of its variance. Simulation studies confirm the quality of our asymptotic approximations and the superior performance of the proposed methodology relative to the accepted standard. Our semi-automated methodology makes it feasible to estimate the radius of gyration many times, from replicated SAXS data under various experimental conditions, in an objective and reproducible manner. This in turn allows for secondary analyses of the dataset of estimates, as we demonstrate with a split–split plot analysis for 357 SAXS intensity curves. Supplementary materials for this article are available online.

笔记与分组