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The observation of the first pulse-to-pulse glitch in the Vela pulsar opens anew window on the internal dynamics of neutron stars. We study the minimalthree-component model for pulsar glitches by solving it with generic initialconditions. The purpose is to use this solution to fit the data of the 2016Vela glitch by employing a Bayesian approach and to obtain a probabilitydistribution for the physical parameters of the model and for observationalparameters, such as the glitch rise time and the relaxation timescale. The fitis achieved through Bayesian inference. Due to the presence of an increase inthe timing residuals near the glitch time, an extra magnetospheric componentwas added to the three-component model to deal with this phenomenon. Aphysically reasonable, non-informative prior was set on the parameters of themodel, so that the posterior distribution could be compared with informationobtained from microphysical calculations. By considering a model with atightened prior on the moment of inertia fractions and by comparing it with theoriginal model by means of Bayesian model selection, we studied the possibilityof a crust-limited superfluid reservoir. We obtained the posterior distributionfor the moment of inertia fractions of the superfluid components, the couplingparameters, and the initial velocity lags between the components. An analysisof the inferred posterior also confirmed the presence of an overshoot in thatglitch and set an upper limit of $\sim 6\,$s on the glitch rise timescale. Thecomparison between the two models with different priors on the moment ofinertia fractions appears to indicate a need for a core participation in theglitch phenomenon, regardless of the uncertain strength of the entrainmentcoupling.

Bayesian estimate of the superfluid moments of inertia from the 2016 glitch in the Vela pulsar