Bayesian Nonparametric Density Autoregression with Lag Selection

21 Mar 2020 Heiner Matthew Kottas Athanasios

We develop a Bayesian nonparametric autoregressive model applied to flexibly estimate general transition densities exhibiting nonlinear lag dependence. Our approach is related to Bayesian density regression using Dirichlet process mixtures, with the Markovian likelihood defined through the conditional distribution obtained from the mixture... (read more)

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