Abstract
We present in this work a new approach to the derivation of galactic parameters via the star counts method. It uses a modern version of the model of Ortiz & Lépine (1993) and the 2MASS data in J, H and K_{S} to estimate, based on a regular grid of lines-of-sight over the whole sky, the most important structural parameters of the Galaxy. It is the first time that the star counts method is used in the whole sky, including the complex region of the galactic plane. We have used a conservative approach to derive parameter values and their uncertainties, and also investigate the effects of using several limiting magnitudes over the best set of parameters which describes the Galaxy. Since the landscape for the figure of merit of a model can be pretty complex when we have a number of free parameters in excess of a dozen, the Markov Chain Monte Carlo method looks like ideal for an overview of the parameter space, to constrain regions of interest for further exploration and to provide realistic uncertainties. The pinpointing of the best parameter values is carried out with the Nested Sampling method, very robust in terms of progression to the optimum solution of a multi-parameter model.
