| 000 | 02020cam a2200253 i 4500 | ||
|---|---|---|---|
| 001 | 17791910 | ||
| 005 | 20250611100354.0 | ||
| 008 | 130626t20132013riua b 001 0 eng | ||
| 020 | _a9781470410544 | ||
| 040 |
_aCSL _cCSL |
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| 041 |
_2eng _aeng |
||
| 084 |
_aB2811 Q3 NBHM _qCSL |
||
| 100 | 1 |
_aEvans, Lawrence C., _eauthor. _9435824 |
|
| 245 | 1 | 3 | _aIntroduction to stochastic differential equations |
| 264 | 1 |
_aProvidence : _bAmerican Mathematical Society, _c2013. |
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| 300 |
_aviii, 151 p. : _bill. ; _c26 cm. |
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| 504 | _aIncludes bibliographical references (pages 147-148) and index. | ||
| 520 | _aThis short book provides a quick, but very readable introduction to stochastic differential equations, that is, to differential equations subject to additive “white noise” and related random disturbances. The exposition is concise and strongly focused upon the interplay between probabilistic intuition and mathematical rigor. Topics include a quick survey of measure theoretic probability theory, followed by an introduction to Brownian motion and the Itô stochastic calculus, and finally the theory of stochastic differential equations. The text also includes applications to partial differential equations, optimal stopping problems and options pricing. This book can be used as a text for senior undergraduates or beginning graduate students in mathematics, applied mathematics, physics, financial mathematics, etc., who want to learn the basics of stochastic differential equations. The reader is assumed to be fairly familiar with measure theoretic mathematical analysis, but is not assumed to have any particular knowledge of probability theory (which is rapidly developed in Chapter 2 of the book). | ||
| 650 | 0 |
_aStochastic differential equations. _9752016 |
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| 650 | 7 |
_aNumerical analysis _9713154 |
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| 650 | 7 |
_aProbability theory and stochastic processes _9812186 |
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| 650 | 7 |
_aNumerical analysis _9713154 |
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| 942 |
_2CC _n0 _cTEXL _hB2811 Q3 NBHM |
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| 999 |
_c1431589 _d1431589 |
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