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Poisson empirical Bayes estimation of sums of random variables via minimum-distance methods
Stefano Favaro, Sandra Fortini, Soham Jana
The estimation of sums of functions of observable and unobservable variables is a long-standing problem in statistics, with applications in many domains. We consider this problem i…
Merging of Bayes and quasi-Bayes empirical Bayes procedures for Poisson compound decisions
Stefano Favaro, Sandra Fortini
The Poisson compound decision problem is a long-standing problem in statistics, in which empirical Bayes methods are used to estimate Poisson means under a mixture model. We study…
Elements of Conformal Prediction
Matteo Sesia, Stefano Favaro
Predictive inference is a fundamental task in statistics, traditionally addressed using parametric assumptions about the data distribution and detailed analyses of how models learn…
Quasi-Bayes empirical Bayes: a sequential approach to the Poisson compound decision problem
Stefano Favaro, Sandra Fortini
The Poisson compound decision problem is a long-standing problem is statistics, for which empirical Bayes methods are commonly used to estimate Poisson means in static or batch set…
Quasi-Bayesian sequential deconvolution
Stefano Favaro, Sandra Fortini
Density deconvolution is the inverse problem of estimating a probability density from observations contaminated by additive noise. Traditionally studied in static or batch settings…