A New Approach to Astronomical Data Analysis Based on Multiple Variables

IF 1.6 4区 物理与天体物理 Q3 ASTRONOMY & ASTROPHYSICS
Prasenjit Banerjee, A. Chattopadhyay, Soumita Modak
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引用次数: 0

Abstract

Data analysis for a sample of celestial bodies generally is preceded by the completeness test in order to verify whether the sample objects are proper representatives of the corresponding part of the universe. A data set following a multivariate, continuous, uniform distribution is said to be “complete in space.” This paper introduces a new approach to check for this completeness for any astronomical data set under a multivariate setup. Our proposed procedure, using the multiple tests of hypotheses based on nonparametric statistics, and consequently, combining their p values, outperforms others from the literature.
基于多变量的天文数据分析新方法
对天体样本进行数据分析之前,通常要进行完备性检验,以验证样本物体是否是宇宙相应部分的适当代表。遵循多元、连续、均匀分布的数据集被称为“空间完备”。本文介绍了一种新的方法来检验多变量设置下任何天文数据集的完整性。我们提出的程序,使用基于非参数统计的假设的多重检验,因此,结合它们的p值,优于文献中的其他程序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Advances in Astronomy
Advances in Astronomy ASTRONOMY & ASTROPHYSICS-
CiteScore
2.70
自引率
7.10%
发文量
10
审稿时长
22 weeks
期刊介绍: Advances in Astronomy publishes articles in all areas of astronomy, astrophysics, and cosmology. The journal accepts both observational and theoretical investigations into celestial objects and the wider universe, as well as the reports of new methods and instrumentation for their study.
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