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Measure, integral and probability

Measure, Integral and Probability is a gentle introduction that makes measure and integration theory accessible to the average third-year undergraduate student. The ideas are developed at an easy pace in a form that is suitable for self-study, with an emphasis on clear explanations and concrete exam...

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Detalles Bibliográficos
Autores principales: Capiński, Marek, Kopp, Peter Ekkehard
Lenguaje:eng
Publicado: Springer 2004
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-1-4471-0645-6
http://cds.cern.ch/record/2023172
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author Capiński, Marek
Kopp, Peter Ekkehard
author_facet Capiński, Marek
Kopp, Peter Ekkehard
author_sort Capiński, Marek
collection CERN
description Measure, Integral and Probability is a gentle introduction that makes measure and integration theory accessible to the average third-year undergraduate student. The ideas are developed at an easy pace in a form that is suitable for self-study, with an emphasis on clear explanations and concrete examples rather than abstract theory. For this second edition, the text has been thoroughly revised and expanded. New features include: · a substantial new chapter, featuring a constructive proof of the Radon-Nikodym theorem, an analysis of the structure of Lebesgue-Stieltjes measures, the Hahn-Jordan decomposition, and a brief introduction to martingales · key aspects of financial modelling, including the Black-Scholes formula, discussed briefly from a measure-theoretical perspective to help the reader understand the underlying mathematical framework. In addition, further exercises and examples are provided to encourage the reader to become directly involved with the material.
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spelling cern-20231722021-04-21T20:14:44Zdoi:10.1007/978-1-4471-0645-6http://cds.cern.ch/record/2023172engCapiński, MarekKopp, Peter EkkehardMeasure, integral and probabilityMathematical Physics and MathematicsMeasure, Integral and Probability is a gentle introduction that makes measure and integration theory accessible to the average third-year undergraduate student. The ideas are developed at an easy pace in a form that is suitable for self-study, with an emphasis on clear explanations and concrete examples rather than abstract theory. For this second edition, the text has been thoroughly revised and expanded. New features include: · a substantial new chapter, featuring a constructive proof of the Radon-Nikodym theorem, an analysis of the structure of Lebesgue-Stieltjes measures, the Hahn-Jordan decomposition, and a brief introduction to martingales · key aspects of financial modelling, including the Black-Scholes formula, discussed briefly from a measure-theoretical perspective to help the reader understand the underlying mathematical framework. In addition, further exercises and examples are provided to encourage the reader to become directly involved with the material.Springeroai:cds.cern.ch:20231722004
spellingShingle Mathematical Physics and Mathematics
Capiński, Marek
Kopp, Peter Ekkehard
Measure, integral and probability
title Measure, integral and probability
title_full Measure, integral and probability
title_fullStr Measure, integral and probability
title_full_unstemmed Measure, integral and probability
title_short Measure, integral and probability
title_sort measure, integral and probability
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-1-4471-0645-6
http://cds.cern.ch/record/2023172
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