Dempster–Shafer Theory and Statistical Inference with Weak Beliefs

Dempster-Shafer Theory and Statistical Inference with Weak Beliefs

The Dempster–Shafer (DS) theory is a powerful tool for probabilistic reasoning based on a formal calculus for combining evidence. DS theory has been widely used in computer science and engineering applications, but has yet to reach the statistical mainstream, perhaps because the DS belief functions do not satisfy long-run frequency properties. Recently, two of the authors proposed an extension ...

Dempster-shafer Inference with Weak Beliefs

Beliefs specified for predicting an unobserved realization of pivotal variables in the context of the fiducial and Dempster-Shafer (DS) inference can be weakened for credible inference. We consider predictive random sets for predicting an unobserved random sample from a known distribution, e.g., the uniform distribution U(0, 1). More specifically, we choose our beliefs for inference in two step...

Statistical Inference Theory

Fundamental Theory of Statistical Inference

statistical inference via empirical bayes approach for stationary and dynamic contingency tables

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