Fig. 6

Likelihood, prior, and posterior for the first 150,000 iterations: This figure demonstrates that each of the seven parallel chains reach an equilibrium point in their output by the end of the 150,000th iteration, during the burn-in phase of the MCMC analysis. The raw output for the likelihood function shows a rapid decrease in sum of squared error within the first 50,000 iterations for each chain, eventually reaching an equilibrium point (A). The sum of integrated muscle excitations (Prior) has some early peaks during the MCMC chain, but also reaches equilibrium by 150,000 iterations (B). Finally, the sum of the likelihood and prior gives the posterior output (C). Note that the MCMC algorithm continues after the end of the plotted data to reach 500,000 iterations total