Non-gaussian likelihood function
I present here a generalization of the maximum likelihood method and the $\chi^2$ method to the cases in which the data are {\it not} assumed to be Gaussian distributed. The method, based on the multivariate Edgeworth expansion, can find several astrophysical applications. I mention only two of them...
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| Main Author: | |
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| Format: | Article (Journal) Chapter/Article |
| Language: | English |
| Published: |
1998
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| In: |
Arxiv
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| Online Access: | Verlag, kostenfrei, Volltext: http://arxiv.org/abs/astro-ph/9810198
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| Author Notes: | Luca Amendola, Osservatorio Astronomico di Roma, Viale del Parco Mellini, 84, Rome 00136 - Italy |
| Summary: | I present here a generalization of the maximum likelihood method and the $\chi^2$ method to the cases in which the data are {\it not} assumed to be Gaussian distributed. The method, based on the multivariate Edgeworth expansion, can find several astrophysical applications. I mention only two of them. First, in the microwave background analysis, where it cannot be excluded that the initial perturbations are non-Gaussian. Second, in the large scale structure statistics, as we already know that the galaxy distribution deviates from Gaussianity on the scales at which non-linearity is important. As a first interesting result I show here how the confidence regions are modified when non-Gaussianity is taken into account. |
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| Item Description: | Gesehen am 21.11.2017 |
| Physical Description: | Online Resource |