Integrated Markov Chain Monte Carlo (MCMC) analysis of primordial
  non-Gaussianity (f_NL) in the recent CMB data
  We have made a Markov Chain Monte Carlo (MCMC) analysis of primordial
non-Gaussianity (f_NL) using the WMAP bispectrum and power spectrum. In our
analysis, we have simultaneously constrained f_NL and cosmological parameters
so that the uncertainties of cosmological parameters can properly propagate to
the f_NL estimation. Investigating the parameter likelihoods deduced from MCMC
samples, we find slight deviation from Gaussian shape, which makes a Fisher
matrix estimation less accurate. Therefore, we have estimated the confidence
interval of f_NL by exploring the parameter likelihood without using the Fisher
matrix. We find that the best-fit values of our analysis make a good agreement
with other results, but the confidence interval is slightly different.
