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Wednesday, May 13, 2020 | History

3 edition of An Introduction to Stochastic Modeling found in the catalog.

An Introduction to Stochastic Modeling

by Mark Pinsky

  • 279 Want to read
  • 11 Currently reading

Published by Academic Press [Imprint], Elsevier Science & Technology Books. in San Diego .
Written in


About the Edition

Annotation

Edition Notes

College Audience Elsevier Science & Technology Books

Other titlesSafari books online.
ContributionsKarlin,Samuel
Classifications
LC ClassificationsQA274
The Physical Object
Format[electronic resource]
ID Numbers
Open LibraryOL25560530M
ISBN 100123814162
ISBN 109780123814166

Ross, Introduction to probability models, , Academic Press. Ross, Simulation, 4th Edition, Academic Press. Taylor and Karlin, An Introduction to stochastic modeling, , . Get this from a library! An introduction to stochastic modeling. [Howard M Taylor; Samuel Karlin] -- "Serving as the foundation for a one-semester course in stochastic processes for students .

  An Introduction to Stochastic Modeling: Edition 4 - Ebook written by Mark Pinsky, Samuel Karlin. Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read An Introduction to Stochastic Modeling: 4/5(1). Interest rate modeling and the pricing of related derivatives remain subjects of increasing importance in financial mathematics and risk management. This book provides an accessible introduction to these topics by a step-by-step presentation of concepts with a focus on explicit calculations. Each chapter is accompanied with exercises and their complete solutions, making the book .

A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Each chapter opens with an illustrative case study, and comprehensive presentations include formulation of models, determination of parameters, analysis, . The book is devoted to the study of important classes of stochastic processes: discrete and continuous time Markov processes, Poisson processes, renewal and regenerative processes, .


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