Probabilistic One-Way Sensitivity Analysis with Multiple Comparators: The Conditional Net Benefit Frontier

Nonparametric frontier analysis with multiple constituencies

Abstract. We introduce a methodology for generalizing Data Envelopment Analysis to incorporate the role and impact of constituencies in the classification of the model’s attributes. Constituencies determine whether entities’ attributes in a DEA study are treated as desirable or undesirable. This extension of DEA is the basis for a methodology to answer questions that arise such as: Which consti...

One-Way Probabilistic Reversible and Quantum One-Counter Automata

Kravtsev introduced 1-way quantum 1-counter automata (1Q1CAs), and showed that several non-context-free languages can be recognized by bounded error 1Q1CAs. In this paper, we rst show that all of these non-context-free languages can be also recognized by bounded error 1PR1CAs (and so 1Q1CAs). Moreover, the accepting probability of each of these 1PR1CAs is strictly greater than, or at least equa...

The Right Frontier Constraint as Conditional

The Right Frontier Constraint (rfc) claims that antecedents are only available for anaphoric reference if they are located at the right hand side of any level of a linearly ordered discourse parse tree. We show that this constraint does hold only under certain conditions — which, however, apply for most circumstances of everyday talk. The data of our analysis in which the rfc does not hold come...

The One-way Analysis of Variance

A Bayesian approach to probabilistic sensitivity analysis in structured benefit-risk assessment.

Quantitative decision models such as multiple criteria decision analysis (MCDA) can be used in benefit-risk assessment to formalize trade-offs between benefits and risks, providing transparency to the assessment process. There is however no well-established method for propagating uncertainty of treatment effects data through such models to provide a sense of the variability of the benefit-risk ...