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dc.contributor.authorKachapova, Fen_NZ
dc.date.accessioned2018-12-10T03:49:28Z
dc.date.available2018-12-10T03:49:28Z
dc.date.copyright2018-11-12en_NZ
dc.identifier.citationJournal of Mathematics and Statistics 2018, Retrieved from: https://thescipub.com/abstract/10.3844/ofsp.12176
dc.identifier.issn1549-3644en_NZ
dc.identifier.urihttp://hdl.handle.net/10292/12109
dc.description.abstractIn this paper we formalize some fundamental concepts of probability theory such as the axiomatic definition of probability space, random variables and their characteristics, in the Calculus of Inductive Constructions, which is a variant of type theory and the foundation for the proof assistant COQ. In a type theory every term and proposition should have a type, so in our formalizations we assign an appropriate type to each object in order to create a framework where further development of formalized probability theory will be possible. Our formalizations are based on mathematical results developed in the COQ standard library; we use mainly the parts with logic and formalized real analysis. In the future we aim to create COQ coding for our formalizations of probability concepts and theorems. In this paper the definitions and some proofs are presented as flag-style derivations while other proofs are more informal.
dc.publisherScience Publications
dc.relation.urihttps://thescipub.com/abstract/10.3844/ofsp.12176en_NZ
dc.rights© 2018 Farida Kachapova. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
dc.subjectType Theory; Kolmogorov's Axiomatics; Probability Theory; Calculus of Inductive Constructions; Flag-Style Derivation
dc.titleFormalizing Probability Concepts in a Type Theoryen_NZ
dc.typeJournal Article
dc.rights.accessrightsOpenAccessen_NZ
dc.identifier.doi10.3844/ofsp.12176en_NZ
aut.relation.pages10
pubs.elements-id350375
aut.relation.journalJournal of Mathematics and Statisticsen_NZ


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