Copula-constructed non-Gaussian likelihoods for weak-lensing correlations match simulations better than Gaussians on large scales, yet produce only negligible shifts in S8 for 10 000 deg² surveys.
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2026 2verdicts
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An approximate multivariate Student-t likelihood is derived for the convolution of an inverse-Wishart-based Student-t with Gaussian errors by matching covariance and multivariate kurtosis.
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The Non-Gaussian Weak-Lensing Likelihood: A Multivariate Copula Construction and Impact on Cosmological Constraints
Copula-constructed non-Gaussian likelihoods for weak-lensing correlations match simulations better than Gaussians on large scales, yet produce only negligible shifts in S8 for 10 000 deg² surveys.
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On combining estimated and analytic covariance matrices
An approximate multivariate Student-t likelihood is derived for the convolution of an inverse-Wishart-based Student-t with Gaussian errors by matching covariance and multivariate kurtosis.