114 citations · 188 across the 8 of their papers we have counts for
9 papers
Coherent Measures of Discrepancy, Uncertainty and Dependence, with Applications to Bayesian Predictive Experimental Design
A. Philip Dawid
We show how, associated with any decision problem, we may derive related functions measuring uncertainty, discrepancy and dependence of distributions. Such "coherent" functions hav…
On Learnability under General Stochastic Processes
A. Philip Dawid, Ambuj Tewari
Statistical learning theory under independent and identically distributed (iid) sampling and online learning theory for worst case individual sequences are two of the best develope…
The Hyvärinen scoring rule in Gaussian linear time series models
Silvia Columbu, Valentina Mameli, Monica Musio +1
Likelihood-based estimation methods involve the normalising constant of the model distributions, expressed as a function of the parameter. However in many problems this function is…
New bounds for the Probability of Causation in Mediation Analysis
Rossella Murtas, Alexander Philip Dawid, Monica Musio
An individual has been subjected to some exposure and has developed some outcome. Using data on similar individuals, we wish to evaluate, for this case, the probability that the ou…
A Note on Bayesian Model Selection for Discrete Data Using Proper Scoring Rules
A. Philip Dawid, Monica Musio, Silvia Columbu
We consider the problem of choosing between parametric models for a discrete observable, taking a Bayesian approach in which the within-model prior distributions are allowed to be…
Comparisons of Hyvärinen and pairwise estimators in two simple linear time series models
Valentina Mameli, Monica Musio, A. Philip Dawid
The aim of this paper is to compare numerically the performance of two estimators based on Hyvärinen's local homogeneous scoring rule with that of the full and the pairwise maximum…
Bayesian Model Selection Based on Proper Scoring Rules
A. Philip Dawid, Monica Musio
Bayesian model selection with improper priors is not well-defined because of the dependence of the marginal likelihood on the arbitrary scaling constants of the within-model prior…
Structural Markov graph laws for Bayesian model uncertainty
Simon Byrne, A. Philip Dawid
This paper considers the problem of defining distributions over graphical structures. We propose an extension of the hyper Markov properties of Dawid and Lauritzen [Ann. Statist. 2…
Theory and Applications of Proper Scoring Rules
A. Philip Dawid, Monica Musio
We give an overview of some uses of proper scoring rules in statistical inference, including frequentist estimation theory and Bayesian model selection with improper priors.