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• W2246804274 abstract "We consider the shape of the posterior distribution to be used when fitting cosmological models to power spectra measured from galaxy surveys. At very large scales, Gaussian posterior distributions in the power do not approximate the posterior distribution |$mathcal {P}_R$| we expect for a Gaussian density field |$delta _{boldsymbol {k}}$|⁠, even if we vary the covariance matrix according to the model to be tested. We compare alternative posterior distributions with |$mathcal {P}_R$|⁠, both mode-by-mode and in terms of expected measurements of primordial non-Gaussianity parametrized by fNL. Marginalising over a Gaussian posterior distribution |$mathcal {P}_{rm f}$| with fixed covariance matrix yields a posterior mean value of fNL which, for a data set with the characteristics of Euclid, will be underestimated by ▵fNL = 0.4, while for the data release 9 of the Sloan Digital Sky Survey-III Baryon Oscillation Spectroscopic Survey (BOSS DR9; Ahn et al.) it will be underestimated by ▵fNL = 19.1. Adopting a different form of the posterior function means that we do not necessarily require a different covariance matrix for each model to be tested: this dependence is absorbed into the functional form of the posterior. Thus, the computational burden of analysis is significantly reduced." @default.
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• W2246804274 date "2015-11-23" @default.
• W2246804274 modified "2023-10-14" @default.
• W2246804274 title "Cosmological parameter inference from galaxy clustering: the effect of the posterior distribution of the power spectrum" @default.
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• W2246804274 doi "https://doi.org/10.1093/mnras/stv2307" @default.
• W2246804274 hasPublicationYear "2015" @default.
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