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Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies
Bayesian variable selection generalized linear models Gaussian processes
2011/7/5
This paper presents a unified treatment of Gaussian process models that extends to data from the exponential dispersion family and to survival data.
Bayesian inference with rescaled Gaussian process priors
Rate of convergence Bayesian inference nonparametric density estimation nonparametric regression classification
2009/9/16
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 scal...
Lower bounds for posterior rates with Gaussian process priors
Bayesian nonparametrics Gaussian process priors Lower bounds
2009/9/16
Upper bounds for rates of convergence of posterior distributions associated to Gaussian process priors are obtained by van der Vaart and van Zanten in [van der Vaart and van Zanten, Rates of contracti...