Flexible Bayesian Inference for Diffusion Processes using Splines

We introduce a flexible method to simultaneously infer both the drift and volatility functions of a discretely observed scalar diffusion. We introduce spline bases to represent these functions and develop a Markov chain Monte Carlo algorithm to infer, a posteriori, the coefficients of these function...

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Veröffentlicht in:	Methodology and computing in applied probability 2023-12, Vol.25 (4), p.83, Article 83
Hauptverfasser:	Jenkins, Paul A., Pollock, Murray, Roberts, Gareth O.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Astrophysics Bayesian analysis Business and Management Datasets Diffusion Drift Economics Electrical Engineering Life Sciences Markov analysis Markov chains Mathematics and Statistics Methods Paleoclimate science Paleoclimatology Spline functions Statistical inference Statistics Volatility
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