An MCMC determination of the primordial helium abundance
  Spectroscopic observations of the chemical abundances in metal-poor H II
regions provide an independent method for estimating the primordial helium
abundance. H II regions are described by several physical parameters such as
electron density, electron temperature, and reddening, in addition to y, the
ratio of helium to hydrogen. It had been customary to estimate or determine
self-consistently these parameters to calculate y. Frequentist analyses of the
parameter space have been shown to be successful in these determinations, and
Markov Chain Monte Carlo (MCMC) techniques have proven to be very efficient in
sampling this parameter space. Nevertheless, accurate determination of the
primordial helium abundance from observations of H II regions is constrained by
both systematic and statistical uncertainties. In an attempt to better reduce
the latter, and better characterize the former, we apply MCMC methods to the
large dataset recently compiled by Izotov, Thuan, & Stasinska (2007). To
improve the reliability of the determination, a high quality dataset is needed.
In pursuit of this, a variety of cuts are explored. The efficacy of the He I
4026 emission line as a constraint on the solutions is first examined,
revealing the introduction of systematic bias through its absence. As a clear
measure of the quality of the physical solution, a \chi^2 analysis proves
instrumental in the selection of data compatible with the theoretical model. In
addition, the method also allows us to exclude systems for which parameter
estimations are statistical outliers. As a result, the final selected dataset
gains in reliability and exhibits improved consistency. Regression to zero
metallicity yields Y_p = 0.2534 \pm 0.0083, in broad agreement with the WMAP
result. The inclusion of more observations shows promise for further reducing
the uncertainty, but more high quality spectra are required.
