  The critical slip distance in rate and state model for fault friction in the
study of potential earthquakes can vary wildly from micrometers to few meters
depending on the length scale of the critically stressed fault. This makes it
incredibly important to construct an inversion framework that provides good
estimates of the critical slip distance purely based on the observed
acceleration at the seismogram. The framework is based on Bayesian inference
and Markov chain Monte Carlo. The synthetic data is generated by adding noise
to the acceleration output of spring-slider-damper idealization of the rate and
state model as the forward model.
