Consistent nonparametric Bayesian inference for discretely observed scalar diffusions

Frank van der Meulen; Harry van Zanten

doi:10.3150/11-bej385

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arXiv · 1301.7567

Consistent nonparametric Bayesian inference for discretely observed scalar diffusions

Frank van der Meulen·Harry van Zanten

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Abstract

We study Bayes procedures for the problem of nonparametric drift estimation for one-dimensional, ergodic diffusion models from discrete-time, low-frequency data. We give conditions for posterior consistency and verify these conditions for concrete priors, including priors based on wavelet expansions.

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Frank van der Meulen, Harry van Zanten. 2013-01-31. Consistent nonparametric Bayesian inference for discretely observed scalar diffusions. https://doi.org/10.3150/11-bej385

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