Stochastic Calculus
Grigoriu, Mircea
Produktnummer:
183dd1fa4d40ed4348ab08b8675f44ee06
Autor: | Grigoriu, Mircea |
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Themengebiete: | Probability theory Simulation Stochastic calculus applications of mathematics ksa numerical mathematics numerical methods partial differential equations stochastic process stochastic processes |
Veröffentlichungsdatum: | 24.09.2002 |
EAN: | 9780817642426 |
Sprache: | Englisch |
Seitenzahl: | 775 |
Produktart: | Gebunden |
Verlag: | Birkhäuser Boston |
Untertitel: | Applications in Science and Engineering |
Produktinformationen "Stochastic Calculus"
Algebraic, differential, and integral equations are used in the applied sciences, en gineering, economics, and the social sciences to characterize the current state of a physical, economic, or social system and forecast its evolution in time. Generally, the coefficients of and/or the input to these equations are not precisely known be cause of insufficient information, limited understanding of some underlying phe nomena, and inherent randonmess. For example, the orientation of the atomic lattice in the grains of a polycrystal varies randomly from grain to grain, the spa tial distribution of a phase of a composite material is not known precisely for a particular specimen, bone properties needed to develop reliable artificial joints vary significantly with individual and age, forces acting on a plane from takeoff to landing depend in a complex manner on the environmental conditions and flight pattern, and stock prices and their evolution in time depend on a large number of factors that cannot be described by deterministic models. Problems that can be defined by algebraic, differential, and integral equations with random coefficients and/or input are referred to as stochastic problems. The main objective of this book is the solution of stochastic problems, that is, the determination of the probability law, moments, and/or other probabilistic properties of the state of a physical, economic, or social system. It is assumed that the operators and inputs defining a stochastic problem are specified.

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