Concerning parameter estimation using the cosmic microwave background

Most parameter constraints obtained from cosmic microwave background (CMB) anisotropy data are based on power estimates and rely on approximate likelihood functions; computational diculties generally preclude an exact analysis based on pixel values. With the specic goal of testing this kind of approach, we have performed a complete (un-approximated) likelihood analysis combining the COBE, Saskatoon and MAX data sets. We examine in detail the ability of certain approximate techniques based on band{power estimates to recover the full likelihood constraints. The traditional 2 {method does not always nd the same best{t model as the likelihood analysis (a bias), due mainly to the false assumption of Gaussian likelihoods that makes the method overly sensitive to data outliers. Although an improvement, other approaches employing non{Gaussian flat-band likelihoods do not always faithfully reproduce the complete likelihood constraints either; not even when using the exact flat-band likelihood curves. We trace this to the neglect of spectral information by simple flat band{power estimates. A straightforward extension incorporating a local eective slope (of the power spectrum, Cl )p rovides a faithful representation of the likelihood surfaces without signicantly increasing computing cost. Finally, we also demonstrate that the best{t model to this particular data set is a good t, or that the observations are consistent with Gaussian sky fluctuations, according to our statistics.

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