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Bayesian Mixtures Of Autoregressive Models, Sally Wood, Ori Rosen, Robert Kohn
Bayesian Mixtures Of Autoregressive Models, Sally Wood, Ori Rosen, Robert Kohn
Sally Wood
In this paper we propose a class of time-domain models for analyzing possibly nonstationary time series. This class of models is formed as a mixture of time series models, whose mixing weights are a function of time. We consider specifically mixtures of autoregressive models with a common but unknown lag. The model parameters, including the number of mixture components, are estimated via Markov chain Monte Carlo methods. The methodology is illustrated with simulated and real data.
Local Spectral Analysis Via A Bayesian Mixture Of Smoothing Splines” Journal Of The American Statistical Association, Sally Wood, Ori Rosen, David Stoffer
Local Spectral Analysis Via A Bayesian Mixture Of Smoothing Splines” Journal Of The American Statistical Association, Sally Wood, Ori Rosen, David Stoffer
Sally Wood
No abstract provided.