AI 中文总结
研究通过间距与双峰软件库进行模态分析，介绍了包含多种测试的R包Dimodal，描述其实现与性能，应用于识别小行星带柯克伍德空隙，还展示了软件端口，如DimodalCPy命令行程序。
AI 中文摘要
间距，即连续顺序统计量之间的差异，具有反映数据模态的两个特征。在模态附近会出现一致、稳定的值，而局部增加则标志着它们之间的转变。这些特征不仅表明多模态，还能定位模态和反模态。双峰是一个用于检测和评估这些情况的R包。它包括用于低通滤波平滑间距的参数特征模型和自举测试、用于区间间距的非参数游程和置换测试，以及原始间距中变化点的融合。我们介绍了该分析，描述了该包、其实现和性能，并将其应用于识别小行星带中的柯克伍德空隙。我们还展示了软件端口，其中DimodalCPy是一个用C编写的带有Python接口的命令行程序。
英文摘要
Spacing, the difference between consecutive order statistics, has two features that reflect the modality of the data. Consistent, stable values occur around modes while local increases mark the transitions between them. These features not only signal multi-modality, they also locate modes and anti-modes. Dimodal is an R package for detecting and evaluating these situations. It includes parametric feature models and bootstrap tests for spacing smoothed by low-pass filtering, non-parametric runs and permutation tests for the interval spacing, and a fusion of changepoints in the raw spacing. We introduce the analysis, describe the package, its implementation and performance, and apply it to identifying Kirkwood gaps in the asteroid belt. We also present ports of the software, with DimodalCPy a command-line program written in C with a Python interface.
CommentsThe ancialliary directory contains an R script for generating the figures and tables for the paper ; v1 - added arXiv numbers to references
