II: Bayesian Methods for Cosmological Parameter Estimation from Cosmic Microwave Background Measurements
Astrophysics
2016-08-30 v1
Abstract
We present a strategy for a statistically rigorous Bayesian approach to the problem of determining cosmological parameters from the results of observations of anisotropies in the cosmic microwave background. Our strategy relies on Markov chain Monte Carlo methods, specifically the Metropolis-Hastings algorithm, to perform the necessary high-dimensional integrals. We describe the Metropolis-Hastings algorithm in detail and discuss the results of our test on simulated data.
Cite
@article{arxiv.astro-ph/0103134,
title = {II: Bayesian Methods for Cosmological Parameter Estimation from Cosmic Microwave Background Measurements},
author = {Nelson Christensen and Renate Meyer and Lloyd Knox and Ben Luey},
journal= {arXiv preprint arXiv:astro-ph/0103134},
year = {2016}
}
Comments
This paper expands on the work presented in astro-ph/0006401, and now includes a test of the method. 15 pages, 1 figure