Regularizing Priors for Linear Inverse Problems *

  title={Regularizing Priors for Linear Inverse Problems *},
  author={Jean-Pierre Florens and Anna De Simoni},
This paper proposes a new Bayesian approach for estimating, nonparametrically, parameters in econometric models that are characterized as the solution of a linear inverse problem. By using a Gaussian process prior distribution we propose the posterior mean as an estimator and prove consistency, in the frequentist sense, of the posterior distribution. Consistency of the posterior distribution provides a frequentist validation of our Bayesian procedure. We show that the minimax rate of… CONTINUE READING


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