A method for comparing non-nested models with application to astrophysical searches for new physics

被引：16

作者：

Algeri, Sara ^{[1
,2
]}

Conrad, Jan ^{[1
,2
,3
]}

van Dyk, David A. ^{[1
]}

机构：

[1] Univ London Imperial Coll Sci Technol & Med, Dept Math, Stat Sect, South Kensington Campus, London SW7 2AZ, England

[2] Stockholm Univ, Dept Phys, AlbaNova, SE-10691 Stockholm, Sweden

[3] Oskar Klein Ctr Cosmoparticle Phys, AlbaNova, SE-10691 Stockholm, Sweden

来源：

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY | 2016年 / 458卷 / 01期

基金：

瑞典研究理事会;

关键词：

astroparticle physics; methods: data analysis; methods: statistical; dark matter;

D O I：

10.1093/mnrasl/slw025

中图分类号：

P1 [天文学];

学科分类号：

0704 ;

摘要：

Searches for unknown physics and decisions between competing astrophysical models to explain data both rely on statistical hypothesis testing. The usual approach in searches for new physical phenomena is based on the statistical likelihood ratio test and its asymptotic properties. In the common situation, when neither of the two models under comparison is a special case of the other i.e. when the hypotheses are non-nested, this test is not applicable. In astrophysics, this problem occurs when two models that reside in different parameter spaces are to be compared. An important example is the recently reported excess emission in astrophysical gamma-rays and the question whether its origin is known astrophysics or dark matter. We develop and study a new, simple, generally applicable, frequentist method and validate its statistical properties using a suite of simulations studies. We exemplify it on realistic simulated data of the Fermi-Large Area Telescope gamma-ray satellite, where non-nested hypotheses testing appears in the search for particle dark matter.

引用

页码：L84 / L88

页数：5

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