Markov chain Monte Carlo posterior sampling with the Hamiltonian method

@inproceedings{Hanson2001MarkovCM,
  title={Markov chain Monte Carlo posterior sampling with the Hamiltonian method},
  author={Kenneth M. Hanson},
  booktitle={Medical Imaging: Image Processing},
  year={2001}
}
The Markov Chain Monte Carlo technique provides a means for drawing random samples from a target probability density function (pdf). MCMC allows one to assess the uncertainties in a Bayesian analysis described by a numerically calculated posterior distribution. This paper describes the Hamiltonian MCMC technique in which a momentum variable is introduced for each parameter of the target pdf. In analogy to a physical system, a Hamiltonian H is defined as a kinetic energy involving the momenta… CONTINUE READING
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