摘要：Our primary goal is to obtain a smoothed summary estimate of the
magnetic eld generated in and near to the Milky Way by using Faraday rotation
measures (RM's). Each RM in our data set provides an integrated measure of the
e
ect of the magnetic eld along the entire line of sight to an extragalactic radio
source. The ability to estimate the magnetic eld generated locally by our galaxy
and its environs will help astronomers distinguish local versus distant properties of
the universe. RM's can be considered analogous to geostatistical data on a sphere.
In order to model such data, we employ a Bayesian process convolution approach
which uses Markov chain Monte Carlo (MCMC) for estimation and prediction.
Complications arise due to contamination in the RM measurements, and we resolve
these by means of a mixture prior on the errors.
关键词：Markov chain Monte Carlo, Gaussian process, error mixture model,
spatial model
