  We present a fast Markov Chain Monte-Carlo exploration of cosmological
parameter space. We perform a joint analysis of results from recent CMB
experiments and provide parameter constraints, including sigma_8, from the CMB
independent of other data. We next combine data from the CMB, HST Key Project,
2dF galaxy redshift survey, supernovae Ia and big-bang nucleosynthesis. The
Monte Carlo method allows the rapid investigation of a large number of
parameters, and we present results from 6 and 9 parameter analyses of flat
models, and an 11 parameter analysis of non-flat models. Our results include
constraints on the neutrino mass (m_nu < 0.3eV), equation of state of the dark
energy, and the tensor amplitude, as well as demonstrating the effect of
additional parameters on the base parameter constraints. In a series of
appendices we describe the many uses of importance sampling, including
computing results from new data and accuracy correction of results generated
from an approximate method. We also discuss the different ways of converting
parameter samples to parameter constraints, the effect of the prior, assess the
goodness of fit and consistency, and describe the use of analytic
marginalization over normalization parameters.
