Consistent nonparametric Bayesian inference for discretely observed scalar diffusions

F.H. Meulen, van der, J.H. Zanten, van

Research output: Contribution to journalArticleAcademicpeer-review

14 Citations (Scopus)
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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. Keywords: Bayesian nonparametrics; drift function; posterior consistency; posterior distribution; stochastic differential equations; wavelets
Original languageEnglish
Pages (from-to)44-63
Number of pages20
JournalBernoulli
Volume19
Issue number1
DOIs
Publication statusPublished - 2013

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