Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?"
arXiv:1811.10275
Abstract
This article is the rejoinder for the paper "Probabilistic Integration: A Role in Statistical Computation?" to appear in Statistical Science with discussion. We would first like to thank the reviewers and many of our colleagues who helped shape this paper, the editor for selecting our paper for discussion, and of course all of the discussants for their thoughtful, insightful and constructive comments. In this rejoinder, we respond to some of the points raised by the discussants and comment further on the fundamental questions underlying the paper: (i) Should Bayesian ideas be used in numerical analysis?, and (ii) If so, what role should such approaches have in statistical computation?
arXiv commentAccepted to Statistical Science
References in corpus (5)
- Gaussian Processes and Kernel Methods: A Review on Connections and Equivalences
- Probabilistic Numerical Methods for PDE-constrained Bayesian Inverse Problems
- Fast Automatic Bayesian Cubature Using Lattice Sampling
- Convergence guarantees for kernel-based quadrature rules in misspecified settings
- Bayesian Quadrature for Multiple Related Integrals