Computational Statistics

, Volume 20, Issue 2, pp 265-273

First online:

Componentwise adaptation for high dimensional MCMC

  • Heikki HaarioAffiliated withUniversity of Helsinki Department of Mathematics and Statistics, University of Helsinki
  • , Eero SaksmanAffiliated withUniversity of Jyväskylä Department of Mathematics and Statistics, University of Jyväskylä
  • , Johanna TamminenAffiliated withFinnish Meteorological Institute Geophysical Research Division

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We introduce a new adaptive MCMC algorithm, based on the traditional single component Metropolis-Hastings algorithm and on our earlier adaptive Metropolis algorithm (AM). In the new algorithm the adaption is performed component by component. The chain is no more Markovian, but it remains ergodic. The algorithm is demonstrated to work well in varying test cases up to 1000 dimensions.


MCMC adaptive MCMC Metropolis-Hastings algorithm