Fig. 1From: Comparison between the Hamiltonian Monte Carlo method and the Metropolis–Hastings method for coseismic fault model estimationExample of sampling using the Hamiltonian Monte Carlo (HMC) method. This figure shows the exploration of a mean parameter of a simple normal distribution from synthetic gaussian data \(\left( {f\left( {\theta {\text{|d}}} \right) \propto {\text{exp}}\left( { - \theta^{2} } \right)} \right)\). The contours show the constant Hamiltonian and their values. Triangles, circles, and squares show the start points, transition points, and end points of each leapfrog transition, respectively. The blue triangle particularly represents the initial point of the sampling. In addition, the orange line shows the jump to the next momentum generated by standard normal distribution after acceptance of the candidate pointBack to article page