Hamiltonian Monte Carlo (HMC)

Hamiltonian Monte Carlo (HMC) sampling method.

References

The original paper, that introduced this method is described in:

1. Simon Duane, Anthony D. Kennedy, Brian J. Pendleton and Duncan Roweth (1987). "Hybrid Monte Carlo". Physics Letters B. 195 (2): 216–222.

Several implementation details are given in:

2. Radford M. Neal (1996). "Monte Carlo Implementation". Bayesian Learning for Neural Networks. Springer. pp. 55–98.

The generalized sampling approach is described in:

3. Francis J. Alexander, Gregory L. Eyink and Juan M. Restrepo (2005). "Accelerated Monte Carlo for Optimal Estimation of Time Series", Journal of Statistical Physics, vol.119, pp: 1331-1345.

Requirements

To ensure smooth execution please install the required modules with:

  $ pip install -r requirements.txt

Examples

Some example on how to use this method can be found below:

1. Rosenbrock
2. Multivariate Normal
3. Ornstein-Uhlenbeck process