Possibility theory and conditional probability offer complementary perspectives for modelling uncertainty, with each framework contributing distinct advantages. Possibility theory, rooted in fuzzy set ...

This is a preview. Log in through your library . Abstract Consider a random vector U whose distribution function coincides in its upper tail with that of an Archimedean copula. We report the fact that ...

We consider two recent approaches to characterizing the manifest probabilities of a strictly unidimensional latent variable representation (one satisfying local independence and response curve ...

Studies axioms, counting formulas, conditional probability, independence, random variables, continuous and discrete distribution, expectation, moment generating functions, law of large numbers, ...

The purpose of the course is to introduce the statistical methods that are critical in the performance analysis and selection of information systems and networks. It includes fundamental topics as ...

The purpose of the course is to introduce the statistical methods that are critical in the performance analysis and selection of information systems and networks. It includes fundamental topics as ...

Probability is the theory that allows us to make an inference from a sample to a population. It provides the mathematical and theoretical basis for quantifying uncertainty. Probability is also used ...

This course is available on the BSc in Data Science, BSc in Mathematics with Data Science and BSc in Mathematics, Statistics and Business. This course is available as an outside option to students on ...

Studies axioms, counting formulas, conditional probability, independence, random variables, continuous and discrete distribution, expectation, joint distributions, moment generating functions, law of ...

This course is compulsory on the BSc in Mathematics, Statistics and Business. This course is available on the BSc in Data Science, BSc in Mathematics with Data Science, Erasmus Reciprocal Programme of ...