  High resolution observations have permitted to resolve the solar
prominences/filaments as sets of threads/fibrils. However, the values of the
physical parameters of these threads and their structuring remain poorly
constrained. We use prominence seismology techniques to analyse transverse
oscillations in threads through the comparison between magnetohydrodynamic
(MHD) models and observations. We apply Bayesian methods to obtain two
different types of information. We first infer the marginal posterior
distribution of physical parameters, such as the magnetic field strength or the
length of the thread, when a totally filled tube, a partially filled tube, and
three damping models (resonant absorption in the Alfv\'en continuum, resonant
absorption in the slow continuum, and Cowling's diffusion) are considered as
certain. Then, we compare the relative plausibility between alternative MHD
models by computing the Bayes factors. Well constrained probability density
distributions can be obtained for the magnetic field strength, the length of
the thread, the density contrast, and parameters associated to damping models.
When comparing the damping models of resonant absorption in the Alfv\'en
continuum, resonant absorption in the slow continuum and Cowling's diffusion
due to partial ionisation of prominence plasma, the resonant absorption in the
Alfv\'en continuum is the most plausible mechanism in explaining the existing
observations. Relations between periods of fundamental and first overtone kink
modes with values around 1 are better explained by expressions of the period
ratio in the long thread approximation, while the rest of the values are more
probable in the short thread limit for the period ratio. Our results show that
Bayesian analysis offers valuable methods for performing parameter inference
and model comparison in the context of prominence seismology.
