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We have made a Markov Chain Monte Carlo (MCMC) analysis of primordialnon-Gaussianity (f_NL) using the WMAP bispectrum and power spectrum. In ouranalysis, we have simultaneously constrained f_NL and cosmological parametersso that the uncertainties of cosmological parameters can properly propagate tothe f_NL estimation. Investigating the parameter likelihoods deduced from MCMCsamples, we find slight deviation from Gaussian shape, which makes a Fishermatrix estimation less accurate. Therefore, we have estimated the confidenceinterval of f_NL by exploring the parameter likelihood without using the Fishermatrix. We find that the best-fit values of our analysis make a good agreementwith other results, but the confidence interval is slightly different.

Integrated Markov Chain Monte Carlo (MCMC) analysis of primordial non-Gaussianity (f_NL) in the recent CMB data