A multiple-valued function f : X → QQ(Y ) is essentially a rule assigning Q unordered and non necessarily distinct elements of Y to each element of X. We study the Lipschitz extension problem in this context by using two general Lipschitz extension theorems recently proved by U. Lang and T. Schlichenmaier. We prove that the pair ` X,QQ(Y ) ́ has the Lipschitz extension property if Y is a Banach ...

We present two prudent semantics within Dung’s theory of argumentation. They are based on two new notions of extension, referred to as p-extension and c-extension. Two arguments cannot belong to the same p-extension whenever one of them attacks indirectly the other one. Two arguments cannot belong to the same c-extension whenever one of them indirectly attacks a third argument while the other o...

In this paper a method to extend discrete uninorms and nullnorms on the finite chain L = {0, . . . , n}, to uninorms and nullnorms defined on the set of discrete fuzzy numbers whose support is a set of consecutive natural numbers contained in L is presented. Some basic properties of discrete uninorms and nullnorms are preserved by this extension method and the structure of these kinds of aggreg...

Random-effects meta-analyses are very commonly used in medical statistics. Recent methodological developments include multivariate (multiple outcomes) and network (multiple treatments) meta-analysis. Here, we provide a new model and corresponding estimation procedure for multivariate network meta-analysis, so that multiple outcomes and treatments can be included in a single analysis. Our new mu...

The spectrum of possible parameters of symmetric configurations is investigated. We propose some new constructions, mainly based on Finite Geometry and on extension methods. New parameters are provided, both for general symmetric configurations and for cyclic symmetric configurations. For several values of k, new upper bounds on the minimum integer E such that for each v≥ E there exists a (cycl...

We discuss the issue of conditioning on events with probability zero within an imprecise-probabilistic setting, where it may happen that the conditioning event has lower probability zero, but positive upper probability. In this situation, two different conditioning rules are commonly used: regular extension and natural extension. We explain the difference between them and discuss various techni...