# Comment on "Probabilistic Integration: A Role in Statistical Computation?"

## TL;DR

This paper discusses the assumptions and implementation challenges of automatic Bayesian cubature, a probabilistic integration method that determines when a simulation has achieved a desired error tolerance with high confidence.

## Contribution

It provides critical commentary on the modeling assumptions and practical issues in designing automatic Bayesian cubature methods.

## Key findings

- Highlights key modeling assumptions in probabilistic integration.
- Identifies implementation challenges in automatic Bayesian cubature.
- Discusses the criteria for stopping simulations based on confidence levels.

## Abstract

Probabilistic integration provides a criterion for stopping a simulation when a specified error tolerance is satisfied with high confidence. We comment on some of the modeling assumptions and implementation issues involved in designing an automatic Bayesian cubature.