Astronomy and Astrophysics – Astrophysics
Scientific paper
2002-03-15
Mon.Not.Roy.Astron.Soc. 335 (2002) 377
Astronomy and Astrophysics
Astrophysics
12 pages, 6 figures, submitted to MNRAS
Scientific paper
10.1046/j.1365-8711.2002.05614.x
A method is presented for performing joint analyses of cosmological datasets, in which the weight assigned to each dataset is determined directly by it own statistical properties. The weights are considered in a Bayesian context as a set of hyperparameters, which are then marginalised over in order to recover the posterior distribution as a function only of the cosmological parameters of interest. In the case of a Gaussian likelihood function, this marginalisation may be performed analytically. Calculation of the Bayesian evidence for the data, with and without the introduction of hyperparameters, enables a direct determination of whether the data warrant the introduction of weights into the analysis; this generalises the standard likelihood ratio approach to model comparison. The method is illustrated by application to the classic toy problem of fitting a straight line to a set of data. A cosmological illustration of the technique is also presented, in which the latest measurements of the cosmic microwave background power spectrum are used to infer constraints on cosmological parameters.
Bridle Sarah L.
Hobson Michael P.
Lahav Ofer
No associations
LandOfFree
Combining cosmological datasets: hyperparameters and Bayesian evidence does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Combining cosmological datasets: hyperparameters and Bayesian evidence, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Combining cosmological datasets: hyperparameters and Bayesian evidence will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-143853