English

Non-Gaussian inference from non-linear and non-Poisson biased distributed data

Cosmology and Nongalactic Astrophysics 2014-07-01 v1

Abstract

We study the statistical inference of the cosmological dark matter density field from non-Gaussian, non-linear and non-Poisson biased distributed tracers. We have implemented a Bayesian posterior sampling computer-code solving this problem and tested it with mock data based on N-body simulations.

Keywords

Cite

@article{arxiv.1406.7796,
  title  = {Non-Gaussian inference from non-linear and non-Poisson biased distributed data},
  author = {Metin Ata and Francisco-Shu Kitaura and Volker Müller},
  journal= {arXiv preprint arXiv:1406.7796},
  year   = {2014}
}

Comments

Proceedings of IAU 306 Symposium, Statistical Challenges of the 21st Century Cosmology

R2 v1 2026-06-22T04:51:31.337Z