An Introduction to Stochastic Modeling PDF Download
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Author: Howard M. Taylor
Publisher: Academic Press
ISBN: 1483269272
Category : Mathematics
Languages : en
Pages : 410
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Book Description
An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.
Author: Howard M. Taylor
Publisher: Academic Press
ISBN: 1483269272
Category : Mathematics
Languages : en
Pages : 410
Get Book Here
Book Description
An Introduction to Stochastic Modeling provides information pertinent to the standard concepts and methods of stochastic modeling. This book presents the rich diversity of applications of stochastic processes in the sciences. Organized into nine chapters, this book begins with an overview of diverse types of stochastic models, which predicts a set of possible outcomes weighed by their likelihoods or probabilities. This text then provides exercises in the applications of simple stochastic analysis to appropriate problems. Other chapters consider the study of general functions of independent, identically distributed, nonnegative random variables representing the successive intervals between renewals. This book discusses as well the numerous examples of Markov branching processes that arise naturally in various scientific disciplines. The final chapter deals with queueing models, which aid the design process by predicting system performance. This book is a valuable resource for students of engineering and management science. Engineers will also find this book useful.
Author: William T. Ziemba
Publisher: World Scientific
ISBN: 981256800X
Category : Business & Economics
Languages : en
Pages : 756
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Book Description
A reprint of one of the classic volumes on portfolio theory and investment, this book has been used by the leading professors at universities such as Stanford, Berkeley, and Carnegie-Mellon. It contains five parts, each with a review of the literature and about 150 pages of computational and review exercises and further in-depth, challenging problems.Frequently referenced and highly usable, the material remains as fresh and relevant for a portfolio theory course as ever.
Author: Timothy Michael Devinney
Publisher: Free Press
ISBN:
Category : Business & Economics
Languages : en
Pages : 440
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Book Description
Author: Morton I. Kamien
Publisher: Courier Corporation
ISBN: 0486310280
Category : Mathematics
Languages : en
Pages : 402
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Book Description
Since its initial publication, this text has defined courses in dynamic optimization taught to economics and management science students. The two-part treatment covers the calculus of variations and optimal control. 1998 edition.
Author: Shai Shalev-Shwartz
Publisher: Cambridge University Press
ISBN: 1107057132
Category : Computers
Languages : en
Pages : 415
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Book Description
Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
Author: Sebastian Klapdor
Publisher: Springer Science & Business Media
ISBN: 3658017325
Category : Business & Economics
Languages : en
Pages : 146
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Book Description
Internet advertising has come off age; yet little is known in research and practice about how digital channel advertising really works. The empirical research in this thesis intends to fill this gap and shed light on the effectiveness of online advertising. Two studies are conducted that focus on multichannel online advertising and search engine advertising, the single-most important online ad channel. In an interdisciplinary approach, both studies first develop comprehensive theoretical models based on existing work in related research fields—for example, marketing and information retrieval. This approach pays off and leads to new and insightful findings: - There are synergies in multichannel online advertising: purchase propensity increases when consumers receive advertising messages through multiple channels. - The channel order can influence the conversion probability. - Click-through rates in search engine advertising are influenced through various keyword criteria on semantic and syntactic level The results of this thesis constitute an important starting point for future research in online advertising. Furthermore, the results enable practitioners to improve the effectiveness of online advertising through a more differentiated campaign management approach. Based on its findings, the thesis outlines how a future integrated approach to online advertising could look like.
Author:
Publisher:
ISBN:
Category : Dissertations, Academic
Languages : en
Pages : 524
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Book Description
Author: Daniel P. Heyman
Publisher: Courier Corporation
ISBN: 9780486432601
Category : Mathematics
Languages : en
Pages : 580
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Book Description
This two-volume set of texts explores the central facts and ideas of stochastic processes, illustrating their use in models based on applied and theoretical investigations. They demonstrate the interdependence of three areas of study that usually receive separate treatments: stochastic processes, operating characteristics of stochastic systems, and stochastic optimization. Comprehensive in its scope, they emphasize the practical importance, intellectual stimulation, and mathematical elegance of stochastic models and are intended primarily as graduate-level texts.
Author: David Colander
Publisher: Cambridge University Press
ISBN: 1139459058
Category : Business & Economics
Languages : en
Pages : 33
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Book Description
Macroeconomics is evolving in an almost dialectic fashion. The latest evolution is the development of a new synthesis that combines insights of new classical, new Keynesian and real business cycle traditions into a dynamic, stochastic general equilibrium (DSGE) model that serves as a foundation for thinking about macro policy. That new synthesis has opened up the door to a new antithesis, which is being driven by advances in computing power and analytic techniques. This new synthesis is coalescing around developments in complexity theory, automated general to specific econometric modeling, agent-based models, and non-linear and statistical dynamical models. This book thus provides the reader with an introduction to what might be called a Post Walrasian research program that is developing as the antithesis of the Walrasian DSGE synthesis.
Author: Edward A. Bender
Publisher: Courier Corporation
ISBN: 0486137120
Category : Mathematics
Languages : en
Pages : 273
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Book Description
Employing a practical, "learn by doing" approach, this first-rate text fosters the development of the skills beyond the pure mathematics needed to set up and manipulate mathematical models. The author draws on a diversity of fields — including science, engineering, and operations research — to provide over 100 reality-based examples. Students learn from the examples by applying mathematical methods to formulate, analyze, and criticize models. Extensive documentation, consisting of over 150 references, supplements the models, encouraging further research on models of particular interest. The lively and accessible text requires only minimal scientific background. Designed for senior college or beginning graduate-level students, it assumes only elementary calculus and basic probability theory for the first part, and ordinary differential equations and continuous probability for the second section. All problems require students to study and create models, encouraging their active participation rather than a mechanical approach. Beyond the classroom, this volume will prove interesting and rewarding to anyone concerned with the development of mathematical models or the application of modeling to problem solving in a wide array of applications.
