Bayesian reconstructions and predictions of nonlinear dynamical systems via the hybrid Monte Carlo scheme

DOI10.1016/J.SIGPRO.2004.09.007zbMath1148.37313OpenAlexW2030110735MaRDI QIDQ956124

Takayuki Kurihara, Takashi Matsumoto, Kuniaki Yosui, Yohei Nakada

Publication date: 25 November 2008

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2004.09.007

zbMATH Keywords

Markov chain Monte Carlohybrid Monte CarloBayesian nonlinear time series predictionerror barpredictive meanreconstruction of nonlinear dynamical systems

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Time series analysis of dynamical systems (37M10)

Related Items (3)

System identification using autoregressive Bayesian neural networks with nonparametric noise models ⋮ Joint reconstruction and prediction\break of random dynamical systems under\break borrowing of strength ⋮ A Bayesian nonparametric approach to reconstruction and prediction of random dynamical systems

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