Titlebook: Combining, Modelling and Analyzing Imprecision, Randomness and Dependence; Jonathan Ansari,Sebastian Fuchs,Olgierd Hryniewicz Conference p

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,Sharp Polynomial Upper Bound on?the?Variance,can be carried out in polynomial time in the worst case. For a whole class of interval data this bound is exact as it can be shown that it coincides with the maximum. The algorithm derives from posing the optimisation problem in probabilistic terms, i.e. thinking beyond the deterministic interpretat

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,Hierarchical Clustering and?CoClust Algorithm: A Nested Procedure to?Analyse Sustainable Heating Daon concerning the buildings energy profile. The idea is to use the hierarchical clustering algorithm based on the Gower’s index to find a first partition of buildings based on their static characteristics, such as age class, energy class, and heating surface, and, next, to investigate the within-clu

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On Topologically Typical Bivariate Extreme Value Copulas,nt, we prove that even the subclass of all mutually completely dependent copulas with full support are typical (co-meager). Additionally, considering the subclass of Extreme Value copulas, working with so called Pickands dependence measures, i.e., univariate probability measures with expected value

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,Semi-supervised Learning Guided by?the?Generalized Bayes Rule Under Soft Revision,rion for pseudo-label selection (PLS) in semi-supervised learning. Opposed to traditional methods for PLS we use credal sets of priors (“generalized Bayes”) to represent the epistemic modeling uncertainty. These latter are then updated by the Gamma-Maximin method with soft revision. We eventually se

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,Dissimilarity-Based Clustering with?Soft Proximity Constraints,ty measure that takes into account soft proximity constraints is introduced and its properties are illustrated. Furthermore, some recent issues that are particularly of interest for the analysis of geo-referenced data are discussed.

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,Causal Markov Categories and?Possibility Theory,ion of) Markov kernels, rather than measurable mappings, as primitive. Our aim is to bring researchers in possibility theory and other uncertainty formalism into contact with Markov categories by explaining how the categorical formalism applies in this context as well. We note that, under any contin

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,Sensitivity Analysis on?the?Choice of?the?Metric on?Cronbach’s , Coefficient for?Interval-Valued Dasuring imprecise human traits. Thus, new statistical techniques are being developed to analyze this type of data. In this respect, when items in a construct allow respondents to make use of interval-valued scales, the internal consistency reliability can be quantified by means of an extension of the