Approximate confidence distribution computing (ACDC) offers a new take on the rapidly developing field of likelihood-free inference from within frequentist framework. The appeal this computational method for statistical hinges upon concept distribution, special type estimator which is defined with respect to repeated sampling principle. An ACDC provides validation in problems unknown or intract...

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We develop a statistical process for determining a confidence set for an unknown bipartite matching. It requires only modest assumptions on the nature of the distribution of the data. The confidence set involves a set of linear constraints on the bipartite matching, which permits efficient analysis of the matched data, e.g., using linear regression, while maintaining the proper degree of uncert...

In previous papers, we asserted that software system safety is primarily concerned with epistemic questions, that is, questions concerning knowledge and the degree of confidence that can be placed in that knowledge. We also enumerated a set of 21 foundational epistemic questions, discussed some of the difficulties that exist in answering these questions adequately today, and speculated briefly ...

The field of sensor fusion is well developed, but approaches to describing the confidence one ought to have in the fused result as a function of the confidence one has in the individual measurements is not. This speculative paper is intended to stimulate discussion in the robotics and instrumentation communities regarding how to approach “confidence fusion” in a way that can be practically appl...