For a PDF version of the article, click
For a PDF version of the article, click here.
Abstract. Constraints on cosmological parameters depend on the set of parameters chosen to define the model which is compared with observational data. I use the Akaike and Bayesian information criteria to carry out cosmological model selection, in order to determine the parameter set providing the preferred fit to the data. Applying the information criteria to the current cosmological data sets indicates, for example, that spatially-flat models are statistically preferred to closed models, and that possible running of the spectral index has lower significance than inferred from its confidence limits. I also discuss some problems of statistical assessment arising from there being a large number of `candidate' cosmological parameters that can be investigated for possible cosmological implications, and argue that 95% confidence is too low a threshold to robustly identify the need for new parameters in model fitting. The best present description of cosmological data uses a scale-invariant (n = 1) spectrum of gaussian adiabatic perturbations in a spatially-flat Universe, with the cosmological model requiring only five fundamental parameters to fully specify it.
Keywords: cosmology: theory
Table of Contents