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|a 9780817644284
|9 978-0-8176-4428-4
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|a 10.1007/b138900
|2 doi
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|a T57-57.97
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|a Capasso, Vincenzo.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a An Introduction to Continuous-Time Stochastic Processes
|h [electronic resource] :
|b Theory, Models, and Applications to Finance, Biology, and Medicine /
|c by Vincenzo Capasso, David Bakstein.
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250 |
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|a 1st ed. 2005.
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264 |
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|a Boston, MA :
|b Birkhäuser Boston :
|b Imprint: Birkhäuser,
|c 2005.
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300 |
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|a XIV, 344 p. 13 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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|a Modeling and Simulation in Science, Engineering and Technology,
|x 2164-3725
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|a The Theory of Stochastic Processes -- Fundamentals of Probability -- Stochastic Processes -- The Itô Integral -- Stochastic Differential Equations -- The Applications of Stochastic Processes -- Applications to Finance and Insurance -- Applications to Biology and Medicine.
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520 |
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|a This concisely written book is a rigorous and self-contained introduction to the theory of continuous-time stochastic processes. A balance of theory and applications, the work features concrete examples of modeling real-world problems from biology, medicine, industrial applications, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required. Key topics covered include: * Interacting particles and agent-based models: from polymers to ants * Population dynamics: from birth and death processes to epidemics * Financial market models: the non-arbitrage principle * Contingent claim valuation models: the risk-neutral valuation theory * Risk analysis in insurance An Introduction to Continuous-Time Stochastic Processes will be of interest to a broad audience of students, pure and applied mathematicians, and researchers or practitioners in mathematical finance, biomathematics, biotechnology, and engineering. Suitable as a textbook for graduate or advanced undergraduate courses, the work may also be used for self-study or as a reference. Prerequisites include knowledge of calculus and some analysis; exposure to probability would be helpful but not required since the necessary fundamentals of measure and integration are provided.
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|a Mathematics.
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|a Probabilities.
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|a Mathematical models.
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|a Biomathematics.
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|a Social sciences
|x Mathematics.
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|a Engineering mathematics.
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|a Engineering
|x Data processing.
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|a Applications of Mathematics.
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|a Probability Theory.
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|a Mathematical Modeling and Industrial Mathematics.
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|a Mathematical and Computational Biology.
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|a Mathematics in Business, Economics and Finance.
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650 |
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|a Mathematical and Computational Engineering Applications.
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700 |
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|a Bakstein, David.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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710 |
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|a SpringerLink (Online service)
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773 |
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|t Springer Nature eBook
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|i Printed edition:
|z 9780817670375
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|i Printed edition:
|z 9780817632342
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830 |
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|a Modeling and Simulation in Science, Engineering and Technology,
|x 2164-3725
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|u https://doi.uam.elogim.com/10.1007/b138900
|z Texto Completo
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|a ZDB-2-SMA
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912 |
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|a ZDB-2-SXMS
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|a Mathematics and Statistics (SpringerNature-11649)
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950 |
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|a Mathematics and Statistics (R0) (SpringerNature-43713)
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