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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...
Autores principales: | , |
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Lenguaje: | eng |
Publicado: |
Springer
2004
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-1-4471-0645-6 http://cds.cern.ch/record/2023172 |
_version_ | 1780947016307703808 |
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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. |
id | cern-2023172 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2004 |
publisher | Springer |
record_format | invenio |
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 |
work_keys_str_mv | AT capinskimarek measureintegralandprobability AT kopppeterekkehard measureintegralandprobability |