The specific set of six parameters used to define the cosmological model is somewhat open to choice.
Within the context of fitting a ΛCDM model to a CMB power spectrum, the six selected key parameters are primarily chosen to avoid degeneracies and thus speed convergence of the model fit to the data (Kosowsky et al..
An important subclass of Monte Carlo methods are Markov Chain Monte Carlo (MCMC) methods, defined as those in which the next 'step' in the sequence depends only upon the previous one.
The sequence of steps is then known as a Markov chain..
In fact, one of the guiding principles of Bayesian statistics is that no inference can be made without first specifying prior assumptions, forcing one to question one’s assumptions and state of knowledge before even embarking into a statistical inference problem.
As we shall see, this is currently the situation with cosmological determinations of neutrino masses:
The field of observational cosmology is inevitably intertwined with that of statistics, necessary in order to make sense of the vast amounts of data provided by the Universe.
At this point in our journey, it is therefore useful to review a number of statistical and..
Sociological effects are important as well.
The widespread use of Bayesian parameter inference tools in cosmology, such as:
