Convergence rates of posterior distributions for Brownian semimartingale models

Authors
Publication date 2006
Journal Bernoulli
Volume | Issue number 12 | 5
Pages (from-to) 863-888
Organisations
  • Faculty of Science (FNWI) - Korteweg-de Vries Institute for Mathematics (KdVI)
Abstract We consider the asymptotic behavior of posterior distributions
based on continuous observations from a Brownian semimartingale
model. We present a general result that bounds the posterior
rate of convergence in terms of the complexity of the model and
the amount of prior mass given to balls centered around the true
parameter. This result is illustrated for three special cases of
the model: the Gaussian white-noise model, the perturbed dynamical
system and the ergodic diffusion model. Some examples for specific
priors are discussed as well.
Document type Article
Published at https://doi.org/10.3150/bj/1161614950
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