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020 _a9781493927579
_9978-1-4939-2757-9
024 7 _a10.1007/978-1-4939-2757-9
_2doi
035 _ato000557062
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA273.A1-274.9
050 4 _aQA274-274.9
072 7 _aPBT
_2bicssc
072 7 _aPBWL
_2bicssc
072 7 _aMAT029000
_2bisacsh
082 0 4 _a519.2
_223
100 1 _aCapasso, Vincenzo.
_eauthor.
_9310811
245 1 3 _aAn Introduction to Continuous-Time Stochastic Processes
_helectronic resource
_bTheory, Models, and Applications to Finance, Biology, and Medicine /
_cby Vincenzo Capasso, David Bakstein.
250 _a3rd ed. 2015.
260 _aNew York, NY :
_bSpringer New York :
_bImprint: Birkhäuser,
_c2015.
300 _aXVI, 482 p. 14 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aModeling and Simulation in Science, Engineering and Technology,
_x2164-3679
505 0 _aPart I: Theory of Stochastic Processes -- Fundamentals of Probability -- Stochastic Processes -- The Itô Integral -- Stochastic Differential Equations -- Stability, Stationary, Ergodicity -- Part II: Applications of Stochastic Processes -- Applications to Finance and Insurance -- Applications to Biology and Medicine -- Measure and Integration -- Convergence of Probability Measures on Metric Spaces -- Appendices.
520 _aThis textbook, now in its third edition, offers a rigorous and self-contained introduction to the theory of continuous-time stochastic processes, stochastic integrals, and stochastic differential equations. Expertly balancing 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 include: * Markov processes * Stochastic differential equations * Arbitrage-free markets and financial derivatives * Insurance risk * Population dynamics, and epidemics * Agent-based models New to the Third Edition: * Infinitely divisible distributions * Random measures * Levy processes * Fractional Brownian motion * Ergodic theory * Karhunen-Loeve expansion * Additional applications * Additional  exercises * Smoluchowski  approximation of  Langevin systems An Introduction to Continuous-Time Stochastic Processes, Third Edition will be of interest to a broad audience of students, pure and applied mathematicians, and researchers and practitioners in mathematical finance, biomathematics, biotechnology, and engineering. Suitable as a textbook for graduate or undergraduate courses, as well as European Masters courses (according to the two-year-long second cycle of the “Bologna Scheme”), 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. From reviews of previous editions: "The book is ... an account of fundamental concepts as they appear in relevant modern applications and literature. ... The book addresses three main groups: first, mathematicians working in a different field; second, other scientists and professionals from a business or academic background; third, graduate or advanced undergraduate students of a quantitative subject related to stochastic theory and/or applications." —Zentralblatt MATH.
650 0 _amathematics.
_9566183
650 0 _aEconomics, Mathematical.
_9304111
650 0 _aMathematical models.
_9460208
650 0 _aProbabilities.
_9295556
650 0 _aBiomathematics.
_9460190
650 0 _aApplied mathematics.
_9460111
650 0 _aEngineering mathematics.
_9303575
650 1 4 _aMathematics.
_9566184
650 2 4 _aProbability Theory and Stochastic Processes.
_9303734
650 2 4 _aMathematical Modeling and Industrial Mathematics.
_9303944
650 2 4 _aQuantitative Finance.
_9304891
650 2 4 _aMathematical and Computational Biology.
_9411705
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
_9303577
700 1 _aBakstein, David.
_eauthor.
_9311278
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aModeling and Simulation in Science, Engineering and Technology,
_9306900
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4939-2757-9
912 _aZDB-2-SMA
999 _c411472