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Title: On Bayesian, confidence distribution and frequentist inference Authors:  Erlis Ruli - University of Padova (Italy) [presenting]
Laura Ventura - University of Padova (Italy)
Abstract: The aim is to discuss and characterize connections between frequentist, confidence distribution and objective Bayesian inference, when considering higher-order asymptotics, matching priors, and confidence distributions based on pivotal quantities. The focus is on testing precise or sharp null hypotheses on a scalar parameter of interest. Moreover, we illustrate that the application of these procedures requires little additional effort compared to the application of standard first-order theory. In this respect, using the {\bfseries R} software, we indicate how to perform in practice the computation with two examples in the context of data from inter-laboratory and stress-strength reliability studies.