RJaCGH: Reversible Jump MCMC for the Analysis of CGH Arrays. Bayesian analysis of CGH microarrays fitting Hidden Markov Chain models. The selection of the number of states is made via their posterior probability computed by Reversible Jump Markov Chain Monte Carlo Methods. Also returns probabilistic common regions for gains/losses.
References in zbMATH (referenced in 1 article )
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- Nam, Christopher F.H.; Aston, John A.D.; Johansen, Adam M.: Parallel sequential Monte Carlo samplers and estimation of the number of states in a hidden Markov model (2014)