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

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

Information

Published: February 2013
First available in Project Euclid: 18 January 2013

zbMATH: 1259.62070
MathSciNet: MR3019485
Digital Object Identifier: 10.3150/11-BEJ385

Rights: Copyright © 2013 Bernoulli Society for Mathematical Statistics and Probability

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Vol.19 • No. 1 • February 2013
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