From the 2 of 14 linked papers with an AI index.
8 papers · 1 filter
Bayesian Prediction under Moment Conditioning
Nicholas G. Polson, Daniel Zantedeschi
The paper develops a Bayesian framework for prediction when only moment restrictions are available, using Kullback‑Leibler projection to define a conditional law for blocks of an e…
De Finetti + Sanov = Bayes: Exchangeable Prediction under Moment Constraints
Nicholas G. Polson, Daniel Zantedeschi
The paper studies prediction for exchangeable sequences when only empirical moment constraints are imposed, showing that the limiting predictive distribution is a Bayesian mixture…
E-Values, Bayes Risk, Dual Role of Markov's Inequality
Nicholas G. Polson, Daniel Zantedeschi
Two approaches to hypothesis testing, e-value testing and Bayes risk minimisation, both invoke Markov's inequality to control error probabilities. They differ in which distribution…
A New Look at Bayesian Testing
Jyotishka Datta, Nicholas G. Polson, Vadim Sokolov +1
We identify the critical deviation scale governing Bayesian evidence accumulation in regular parametric testing. Under integrated Bayes risk with zero-one loss, the risk-optimal re…
Bayes Risk for Goodness of Fit Tests
Nicholas G. Polson, Vadim Sokolov, Daniel Zantedeschi
We develop a unified framework for goodness-of-fit (GOF) testing through the lens of Bayes risk. Classical GOF procedures are commonly calibrated either at fixed significance level…
Entropy-Regularized Inference: A Predictive Approach
Nicholas G. Polson, Daniel Zantedeschi
Predictive inference requires balancing statistical accuracy against informational complexity, yet the choice of complexity measure is usually imposed rather than derived. We treat…