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arXiv 1808.01129astro-ph.HE
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银河系双中子星总质量与高斯混合模型选择

Galactic Double Neutron Star total masses and Gaussian mixture model selection

David Keitel

摘要:

Huang等人[arXiv:1804.03101]分析了15颗已知的银河系双中子星(DNS)的总质量。他们建议存在两个子群体,并报告基于似然性的偏好,一个单一的高斯分布的双组分高斯混合模型。本文对该数据集的模型选择提供了一个谨慎的观点:特别是对于这样一个小样本量,纯似然比检验可能会鼓励过度拟合。这可以通过惩罚具有更多自由参数的模型来避免。重新检查高斯混合模型类内的DNS总质量数据集,这可以通过几个简单且完善的统计测试来实现,包括信息标准(AICc,BIC),交叉验证,贝叶斯证据比和惩罚EM测试。虽然这种重新分析证实了基本的发现,即双组分混合物与数据一致,但模型选择标准始终表明,与单组分拟合相比,没有强烈的偏好。将需要更多的DNS发现来解决亚种群的问题。

英文摘要:

Huang et al. [arXiv:1804.03101] have analysed the population of 15 known galactic Double Neutron Stars (DNSs) regarding the total masses of these systems. They suggest the existence of two sub-populations, and report likelihood-based preference for a two-component Gaussian mixture model over a single Gaussian distribution. This note offers a cautionary perspective on model selection for this data set: Especially for such a small sample size, a pure likelihood ratio test can encourage overfitting. This can be avoided by penalising models with a higher number of free parameters. Re-examining the DNS total mass data set within the class of Gaussian mixture models, this can be achieved through several simple and well-established statistical tests, including information criteria (AICc, BIC), cross-validation, Bayesian evidence ratios and a penalised EM-test. While this re-analysis confirms the basic finding that a two-component mixture is consistent with the data, the model selection criteria consistently indicate that there is no robust preference for it over a single-component fit. Additional DNS discoveries will be needed to settle the question of sub-populations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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