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Autor(en): 
  • Sasha Cyganowski
  • Peter Kloeden
  • Jerzy Ombach
  • From Elementary Probability to Stochastic Differential Equations with MAPLE® 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 5-10 Tagen versandfertig
    Veröffentlichung:  November 2001  
    Genre:  Schulbücher 
     
    Algorithmen und Datenstrukturen / Estimator / linearalgebra / MAPLE / Maple (EDV) / measure / numericalmethods / probabilitydistribution
    ISBN:  9783540426660 
    EAN-Code: 
    9783540426660 
    Verlag:  Springer 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Universitext  
    Dimensionen:  H 235 mm / B 155 mm / D 19 mm 
    Gewicht:  505 gr 
    Seiten:  332 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Measure and integration wereonceconsidered,especially by many ofthe more practically inclined, to be an esoteric area ofabstract mathematics best left to pure mathematicians. However,it has become increasingly obvious in recent years that this area is now an indispensable, even unavoidable, language and provides a fundamental methodology for modern probability theory, stochas tic analysis and their applications, especially in financial mathematics. Our aim in writing this book is to provide a smooth and fast introduction to the language and basic results ofmodern probability theory and stochastic differential equations with help ofthe computer manipulator software package MAPLE. It is intended for advanced undergraduate students or graduates, not necessarily in mathematics, to provide an overviewand intuitive background for more advanced studies as wellas somepractical skillsin the use of MAPLE software in the context of probability and its applications. This book is not a conventional mathematics book. Like such books it provides precise definitions and mathematical statements, particularly those based on measure and integration theory, but instead ofmathematical proofs it uses numerous MAPLE experiments and examples to help the reader un derstand intuitively the ideas under discussion. The pace increases from ex tensive and detailed explanations in the first chapters to a more advanced presentation in the latter part of the book. The MAPLE is handled in a sim ilar way, at first with simple commands, then some simple procedures are gardually developed and, finally, the stochastic package is introduced.
      



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