LEADER 05462nam 22008055 450 001 9910299761203321 005 20230810162300.0 010 $a1-4939-2757-4 024 7 $a10.1007/978-1-4939-2757-9 035 $a(CKB)3710000000416770 035 $a(SSID)ssj0001501550 035 $a(PQKBManifestationID)11840173 035 $a(PQKBTitleCode)TC0001501550 035 $a(PQKBWorkID)11446467 035 $a(PQKB)10046176 035 $a(DE-He213)978-1-4939-2757-9 035 $a(MiAaPQ)EBC6315456 035 $a(MiAaPQ)EBC5594825 035 $a(Au-PeEL)EBL5594825 035 $a(OCoLC)1076255866 035 $a(PPN)186030576 035 $a(EXLCZ)993710000000416770 100 $a20150528d2015 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 13$aAn Introduction to Continuous-Time Stochastic Processes $eTheory, Models, and Applications to Finance, Biology, and Medicine /$fby Vincenzo Capasso, David Bakstein 205 $a3rd ed. 2015. 210 1$aNew York, NY :$cSpringer New York :$cImprint: Birkhäuser,$d2015. 215 $a1 online resource (XVI, 482 p. 14 illus.) 225 1 $aModeling and Simulation in Science, Engineering and Technology,$x2164-3725 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a1-4939-2756-6 327 $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. 330 $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. 410 0$aModeling and Simulation in Science, Engineering and Technology,$x2164-3725 606 $aProbabilities 606 $aMathematical models 606 $aSocial sciences$xMathematics 606 $aBiomathematics 606 $aEngineering mathematics 606 $aEngineering$xData processing 606 $aProbability Theory 606 $aMathematical Modeling and Industrial Mathematics 606 $aMathematics in Business, Economics and Finance 606 $aMathematical and Computational Biology 606 $aMathematical and Computational Engineering Applications 615 0$aProbabilities. 615 0$aMathematical models. 615 0$aSocial sciences$xMathematics. 615 0$aBiomathematics. 615 0$aEngineering mathematics. 615 0$aEngineering$xData processing. 615 14$aProbability Theory. 615 24$aMathematical Modeling and Industrial Mathematics. 615 24$aMathematics in Business, Economics and Finance. 615 24$aMathematical and Computational Biology. 615 24$aMathematical and Computational Engineering Applications. 676 $a332 700 $aCapasso$b Vincenzo$4aut$4http://id.loc.gov/vocabulary/relators/aut$051830 702 $aBakstein$b David$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910299761203321 996 $aAn Introduction to Continuous-Time Stochastic Processes$92504060 997 $aUNINA