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Propagation of charged cosmic-rays in the Galaxy depends on the transportparameters, whose number can be large depending on the propagation model underscrutiny. A standard approach for determining these parameters is a manualscan, leading to an inefficient and incomplete coverage of the parameter space.We implement a Markov Chain Monte Carlo (MCMC), which is well suited tomulti-parameter determination. Its specificities (burn-in length, acceptance,and correlation length) are discussed in the phenomenologically well-understoodLeaky-Box Model. From a technical point of view, a trial function based onbinary-space partitioning is found to be extremely efficient, allowing asimultaneous determination of up to nine parameters, including transport andsource parameters, such as slope and abundances. Our best-fit model includesboth a low energy cut-off and reacceleration, whose values are consistent withthose found in diffusion models. A Kolmogorov spectrum for the diffusion slope(delta=1/3) is excluded. The marginalised probability-density function fordelta and alpha (the slope of the source spectra) are delta~0.55-0.60 andalpha~2.14-2.17, depending on the dataset used and the number of freeparameters in the fit. All source-spectrum parameters (slope and abundances)are positively correlated among themselves and with the reaccelerationstrength, but are negatively correlated with the other propagation parameters.A forthcoming study will extend our analysis to more physical diffusion models.

A Markov Chain Monte Carlo for Galactic Cosmic Ray physics: I. Method and results for the Leaky Box Model