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Trans-dimensional Markov chain Monte Carlo; Mixture models; Model selection; Model averaging; Smoothing splines
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Trans-Dimensional Metropolis-Hastings Using Parallel Chains, Sally Wood, James Pullen, Robert Kohn, David Leslie
Trans-Dimensional Metropolis-Hastings Using Parallel Chains, Sally Wood, James Pullen, Robert Kohn, David Leslie
Sally Wood
A general Bayesian sampling method is developed that uses parallel chains to select between models and to average the predictive density over such models. The method applies to both non-nested models and to nested models, and is particularly useful for mixtures of complex component models, where a novel approach to overcome the label-switching problem is used. The method is illustrated with real and simulated data in model-averaging over alternative financial time series models, mixtures of normal distributions, and mixtures of smoothing spline models.