DETECTING BIMODALITY IN ASTRONOMICAL DATASETS
DETECTING BIMODALITY IN ASTRONOMICAL DATASETS
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DOI：
10.1086/117248
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发表时间：
1994-12-01
影响因子：
5.3
通讯作者：
ZEPF, SE
中科院分区：
文献类型：
--
作者：
ASHMAN, KM;BIRD, CM;ZEPF, SE
我们讨论了在天文数据集中检测和量化双峰的统计技术。我们集中在KMM算法，估计双峰在这样的数据集的统计意义和客观的分区数据到子群体。通过模拟双峰分布与一系列的属性，我们研究的敏感性KMM数据集具有不同的特性。我们的研究结果有利于规划的最佳观测策略的双峰被怀疑的系统。混合建模算法类似的KMM算法已被用于在以前的研究中划分成子系统的银河系的恒星人口。我们通过分析球状星团金属丰度分布、星系团中星系的速度分布和伽马射线源爆发持续时间的已发表数据，说明了KMM的广泛适用性。表格和图表的非正式版本，以及KMM的FORTRAN代码和使用说明，可通过匿名FTP从kula.phsx.ukans.edu获得。
We discuss statistical techniques for detecting and quantifying bimodality in astronomical datasets. We concentrate on the KMM algorithm, which estimates the statistical significance of bimodality in such datasets and objectively partitions data into sub-populations. By simulating bimodal distributions with a range of properties we investigate the sensitivity of KMM to datasets with varying characteristics. Our results facilitate the planning of optimal observing strategies for systems where bimodality is suspected. Mixture-modeling algorithms similar to the KMM algorithm have been used in previous studies to partition the stellar population of the Milky Way into subsystems. We illustrate the broad applicability of KMM by analysing published data on globular cluster metallicity distributions, velocity distributions of galaxies in clusters, and burst durations of gamma-ray sources. PostScript versions of the tables and figures, as well as FORTRAN code for KMM and instructions for its use, are available by anonymous ftp from kula.phsx.ukans.edu.