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Application of MCMC to change point detection

July 30, 2008 | Comments Off

Abstract  A nonstandard approach to change point estimation is presented in this paper. Three models with random coefficients and Bayesian
approach are used for modelling the year average temperatures measured in Prague Klementinum. The posterior distribution of
the change point and other parameters are estimated from the random samples generated by the combination of the Metropolis-Hastings
algorithm and the Gibbs sampler.

  • Content Type Journal Article
  • DOI 10.1007/s10492-008-0026-9
  • Authors
    • Jaromír Antoch, Charles University in Prague Faculty of Mathematics and Physics, Department of Statistics Sokolovská 83 186 75 Praha 8-Karlín Czech Republic
    • David Legát, Charles University in Prague Faculty of Mathematics and Physics, Department of Statistics Sokolovská 83 186 75 Praha 8-Karlín Czech Republic