SNIa数据分析中的卡方与中位数统计
Chi-square versus median statistics in SNIa data analysis
摘要：
在本文中，我们比较了卡方和中值似然分析的性能在宇宙学约束的确定使用Ia型超新星的数据。我们使用超新星宇宙学项目的联盟2汇编的307颗超新星进行统计分析，发现卡方统计分析产生更严格的宇宙学约束比中位数统计，如果只考虑超新星数据。我们还表明，当额外的测量被认为是从宇宙微波背景和重子声振荡，合并的宇宙学约束并不强烈依赖于是否适用于卡方统计或中值统计的超新星数据。这表明，当考虑到来自其他宇宙学探测器的互补信息时，卡方和中值统计的性能非常相似，证明了统计分析的鲁棒性。
英文摘要：
In this paper we compare the performances of the chi-square and median likelihood analysis in the determination of cosmological constraints using type Ia supernovae data. We perform a statistical analysis using the 307 supernovae of the Union 2 compilation of the Supernova Cosmology Project and find that the chi-square statistical analysis yields tighter cosmological constraints than the median statistic if only supernovae data is taken into account. We also show that when additional measurements from the Cosmic Microwave Background and Baryonic Acoustic Oscillations are considered, the combined cosmological constraints are not strongly dependent on whether one applies the chi-square statistic or the median statistic to the supernovae data. This indicates that, when complementary information from other cosmological probes is taken into account, the performances of the chi-square and median statistics are very similar, demonstrating the robustness of the statistical analysis.
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