Methodological review demonstrates Bayesian non-parametric framework for time-series data, highlighting how domain knowledge guides Gaussian process design.
In this paper, we offer a gentle introduction to Gaussian processes for time-series data analysis. The conceptual framework of Bayesian modelling for time-series data is discussed and the foundations of Bayesian non-parametric modelling presented for Gaussian processes. We discuss how domain knowledge influences design of the Gaussian process models and provide case examples to highlight the approaches.
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Roberts et al. (2013) studied this question.
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