Bayesian inference with rescaled Gaussian process priors


Abstract: We use rescaled Gaussian processes as prior models for functional parameters in nonparametric statistical models. We show how the rate of contraction of the posterior distributions depends on the scaling factor. In particular, we exhibit rescaled Gaussian process priors yielding posteriors that contract around the true parameter at optimal… (More)


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Citations per Year

Citation Velocity: 12

Averaging 12 citations per year over the last 3 years.

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