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.
Citation
Frank van der Meulen. Harry van Zanten. "Consistent nonparametric Bayesian inference for discretely observed scalar diffusions." Bernoulli 19 (1) 44 - 63, February 2013. https://doi.org/10.3150/11-BEJ385
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