244 citations · 1.5k across the 146 of their papers we have counts for
7 papers · 1 filter
The skewed weak lensing likelihood: why biases arise, despite data and theory being sound
Elena Sellentin, Catherine Heymans, Joachim Harnois-Déraps
We derive the essentials of the skewed weak lensing likelihood via a simple Hierarchical Model. Our likelihood passes four objective and cosmology-independent tests which a standar…
On the use of the Edgeworth expansion in cosmology I: how to foresee and evade its pitfalls
Elena Sellentin, Andrew H. Jaffe, Alan F. Heavens
Non-linear gravitational collapse introduces non-Gaussian statistics into the matter fields of the late Universe. As the large-scale structure is the target of current and future o…
The full-sky relativistic correlation function and power spectrum of galaxy number counts: I. Theoretical aspects
Vittorio Tansella, Camille Bonvin, Ruth Durrer +2
We derive an exact expression for the correlation function in redshift shells including all the relativistic contributions. This expression, which does not rely on the distant-obse…
Massive data compression for parameter-dependent covariance matrices
Alan Heavens, Elena Sellentin, Damien de Mijolla +1
We show how the massive data compression algorithm MOPED can be used to reduce, by orders of magnitude, the number of simulated datasets that are required to estimate the covarianc…
On the insufficiency of arbitrarily precise covariance matrices: non-Gaussian weak lensing likelihoods
Elena Sellentin, Alan F. Heavens
We investigate whether a Gaussian likelihood, as routinely assumed in the analysis of cosmological data, is supported by simulated survey data. We define test statistics, based on…
Marginal Likelihoods from Monte Carlo Markov Chains
Alan Heavens, Yabebal Fantaye, Arrykrishna Mootoovaloo +4
In this paper, we present a method for computing the marginal likelihood, also known as the model likelihood or Bayesian evidence, from Markov Chain Monte Carlo (MCMC), or other sa…