Posterior contraction rates for support boundary recovery

preprint2020arXivOpen access

Abstract

Given a sample of a Poisson point process with intensity λf(x,y)=n1(f(x)≤y),λ_f(x,y) = n \mathbf{1}(f(x) \leq y), we study recovery of the boundary function ff from a nonparametric Bayes perspective. Because of the irregularity of this model, the analysis is non-standard. We establish a general result for the posterior contraction rate with respect to the L1L^1-norm based on entropy and one-sided small probability bounds. From this, specific posterior contraction results are derived for Gaussian process priors and priors based on random wavelet series.

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