Nonparametric Bayesian inference for ergodic diffusions

DOI10.1016/j.jspi.2009.06.003zbMath1183.62144OpenAlexW2117935370MaRDI QIDQ730843

Laura Panzar, Harry van Zanten

Publication date: 1 October 2009

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2009.06.003

zbMATH Keywords

nonparametric Bayesian inferenceGaussian process priorergodic diffusionrate of posterior contraction

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Bayesian inference (62F15) Markov processes: estimation; hidden Markov models (62M05)

Related Items (7)

Reversible jump MCMC for nonparametric drift estimation for diffusion processes ⋮ Nonparametric Bayesian methods for one-dimensional diffusion models ⋮ Consistency of Bayesian nonparametric inference for discretely observed jump diffusions ⋮ Rate-optimal Bayesian intensity smoothing for inhomogeneous Poisson processes ⋮ Parametric estimation from approximate data: non-Gaussian diffusions ⋮ Adaptive estimation of multivariate functions using conditionally Gaussian tensor-product spline priors ⋮ Nonparametric Bayesian drift estimation for multidimensional stochastic differential equations

Cites Work

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• Sharp adaptive estimation of the drift function for ergodic diffusions
• Adaptive Bayesian estimation using a Gaussian random field with inverse gamma bandwidth
• Convergence rates of posterior distributions for Brownian semimartingale models
• Rates of contraction of posterior distributions based on Gaussian process priors
• Convergence rates of posterior distributions for non iid observations
• On the consistency of Bayes estimates
• On uniform laws of large numbers for ergodic diffusions and consistency of estimators
• Adaptive Bayesian inference on the mean of an infinite-dimensional normal distribution
• Convergence rates of posterior distributions.
• Adaptive drift estimation for nonparametric diffusion model.
• Sequential nonparametric adaptive estimation of the drift coefficient in diffusion processes
• Convergence rates for posterior distributions and adaptive estimation
• Lower bounds for posterior rates with Gaussian process priors
• Nonparametric Bayesian model selection and averaging
• On properties of estimators in nonregular situations for Poisson processes
• Misspecification in infinite-dimensional Bayesian statistics
• Nonparametric estimation of the drift coefficient in the diffusion equation
• Nonparametric Identification for Diffusion Processes
• Rates of convergence and asymptotic normality of kernel estimators for ergodic diffusion processes

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