Introduction to Probability Models


Author: Sheldon M. Ross
Publisher: Academic Press
ISBN: 0124081215
Category: Mathematics
Page: 784
View: 9813
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Introduction to Probability Models, Eleventh Edition is the latest version of Sheldon Ross's classic bestseller, used extensively by professionals and as the primary text for a first undergraduate course in applied probability. The book introduces the reader to elementary probability theory and stochastic processes, and shows how probability theory can be applied fields such as engineering, computer science, management science, the physical and social sciences, and operations research. The hallmark features of this text have been retained in this eleventh edition: superior writing style; excellent exercises and examples covering the wide breadth of coverage of probability topic; and real-world applications in engineering, science, business and economics. The 65% new chapter material includes coverage of finite capacity queues, insurance risk models, and Markov chains, as well as updated data. The book contains compulsory material for new Exam 3 of the Society of Actuaries including several sections in the new exams. It also presents new applications of probability models in biology and new material on Point Processes, including the Hawkes process. There is a list of commonly used notations and equations, along with an instructor's solutions manual. This text will be a helpful resource for professionals and students in actuarial science, engineering, operations research, and other fields in applied probability. Updated data, and a list of commonly used notations and equations, instructor's solutions manual Offers new applications of probability models in biology and new material on Point Processes, including the Hawkes process Introduces elementary probability theory and stochastic processes, and shows how probability theory can be applied in fields such as engineering, computer science, management science, the physical and social sciences, and operations research Covers finite capacity queues, insurance risk models, and Markov chains Contains compulsory material for new Exam 3 of the Society of Actuaries including several sections in the new exams Appropriate for a full year course, this book is written under the assumption that students are familiar with calculus

Introduction to Probability Models, Student Solutions Manual (e-only)

Introduction to Probability Models 10th Edition
Author: Sheldon M Ross
Publisher: Academic Press
ISBN: 9780123814364
Category: Mathematics
Page: 170
View: 5220
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Introduction to Probability Models, Student Solutions Manual (e-only)

Introduction to Probability Models, ISE


Author: Sheldon M. Ross
Publisher: Academic Press
ISBN: 0080920179
Category: Mathematics
Page: 800
View: 7196
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Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries. A new section (3.7) on COMPOUND RANDOM VARIABLES, that can be used to establish a recursive formula for computing probability mass functions for a variety of common compounding distributions. A new section (4.11) on HIDDDEN MARKOV CHAINS, including the forward and backward approaches for computing the joint probability mass function of the signals, as well as the Viterbi algorithm for determining the most likely sequence of states. Simplified Approach for Analyzing Nonhomogeneous Poisson processes Additional results on queues relating to the (a) conditional distribution of the number found by an M/M/1 arrival who spends a time t in the system; (b) inspection paradox for M/M/1 queues (c) M/G/1 queue with server breakdown Many new examples and exercises.

Grundbegriffe der Wahrscheinlichkeitsrechnung


Author: A. Kolomogoroff
Publisher: Springer-Verlag
ISBN: 3642498884
Category: Mathematics
Page: 62
View: 1716
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Dieser Buchtitel ist Teil des Digitalisierungsprojekts Springer Book Archives mit Publikationen, die seit den Anfängen des Verlags von 1842 erschienen sind. Der Verlag stellt mit diesem Archiv Quellen für die historische wie auch die disziplingeschichtliche Forschung zur Verfügung, die jeweils im historischen Kontext betrachtet werden müssen. Dieser Titel erschien in der Zeit vor 1945 und wird daher in seiner zeittypischen politisch-ideologischen Ausrichtung vom Verlag nicht beworben.

Philosophischer Versuch über die Wahrscheinlichkeit


Author: Pierre S. de Laplace
Publisher: Harri Deutsch Verlag
ISBN: N.A
Category:
Page: 211
View: 6652
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Introduction to Probability and Statistics for Engineers and Scientists


Author: Sheldon M. Ross
Publisher: Academic Press
ISBN: 0123948428
Category: Mathematics
Page: 686
View: 5811
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Introduction to Probability and Statistics for Engineers and Scientists provides a superior introduction to applied probability and statistics for engineering or science majors. Ross emphasizes the manner in which probability yields insight into statistical problems; ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data sets are incorporated in a wide variety of exercises and examples throughout the book, and this emphasis on data motivates the probability coverage. As with the previous editions, Ross' text has tremendously clear exposition, plus real-data examples and exercises throughout the text. Numerous exercises, examples, and applications connect probability theory to everyday statistical problems and situations. Clear exposition by a renowned expert author Real data examples that use significant real data from actual studies across life science, engineering, computing and business End of Chapter review material that emphasizes key ideas as well as the risks associated with practical application of the material 25% New Updated problem sets and applications, that demonstrate updated applications to engineering as well as biological, physical and computer science New additions to proofs in the estimation section New coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions.

Operations Research

Einführung
Author: Frederick S. Hillier,Gerald J. Liebermann
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3486792083
Category: Business & Economics
Page: 868
View: 6686
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Aus dem Inhalt: Was ist Operations Research? Überblick über die Modellierungsgrundsätze des Operations Research. Einführung in die lineare Programmierung. Die Lösung linearer Programmierungsprobleme: Das Simplexverfahren. Stochastische Prozesse. Warteschlangentheorie. Lagerhaltungstheorie. Prognoseverfahren. Markov-Entscheidungsprozesse. Reliabilität. Entscheidungstheorie. Die Theorie des Simplexverfahrens Qualitätstheorie und Sensitivitätsanalyse Spezialfälle linearer Programmierungsprobleme. Die Formulierung linearer Programmierungsmodelle und Goal-Programmierung. Weitere Algorithmen der linearen Programmierung. Netzwerkanalyse einschließlich PERT-CPM. Dynamische Optimierung. Spieltheorie. Ganzzahlige Programmierung. Nichtlineare Programmierung Simulation. Anhang. Lösungen für ausgewählte Übungsaufgaben.

Survival under Uncertainty

An Introduction to Probability Models of Social Structure and Evolution
Author: Dimitri Volchenkov
Publisher: Springer
ISBN: 3319394215
Category: Science
Page: 238
View: 6588
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This book introduces and studies a number of stochastic models of subsistence, communication, social evolution and political transition that will allow the reader to grasp the role of uncertainty as a fundamental property of our irreversible world. At the same time, it aims to bring about a more interdisciplinary and quantitative approach across very diverse fields of research in the humanities and social sciences. Through the examples treated in this work – including anthropology, demography, migration, geopolitics, management, and bioecology, among other things – evidence is gathered to show that volatile environments may change the rules of the evolutionary selection and dynamics of any social system, creating a situation of adaptive uncertainty, in particular, whenever the rate of change of the environment exceeds the rate of adaptation. Last but not least, it is hoped that this book will contribute to the understanding that inherent randomness can also be a great opportunity – for social systems and individuals alike – to help face the challenge of “survival under uncertainty”.

Applied Probability Models with Optimization Applications


Author: Sheldon M. Ross
Publisher: Courier Corporation
ISBN: 0486318648
Category: Mathematics
Page: 224
View: 2118
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Concise advanced-level introduction to stochastic processes that arise in applied probability. Poisson process, renewal theory, Markov chains, Brownian motion, much more. Problems. References. Bibliography. 1970 edition.

Elementare Wahrscheinlichkeitstheorie und stochastische Prozesse


Author: Kai L. Chung
Publisher: Springer-Verlag
ISBN: 3642670334
Category: Mathematics
Page: 346
View: 355
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Aus den Besprechungen: "Unter den zahlreichen Einführungen in die Wahrscheinlichkeitsrechnung bildet dieses Buch eine erfreuliche Ausnahme. Der Stil einer lebendigen Vorlesung ist über Niederschrift und Übersetzung hinweg erhalten geblieben. In jedes Kapitel wird sehr anschaulich eingeführt. Sinn und Nützlichkeit der mathematischen Formulierungen werden den Lesern nahegebracht. Die wichtigsten Zusammenhänge sind als mathematische Sätze klar formuliert." #FREQUENZ#1

Introduction to Probability Models


Author: Wayne L. Winston
Publisher: Duxbury Press
ISBN: 9780534405786
Category: Business & Economics
Page: 96
View: 997
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The Student Solutions Manual includes solutions to selected problems in the book.

Introduction to Stochastic Dynamic Programming


Author: Sheldon M. Ross
Publisher: Academic Press
ISBN: 1483269094
Category: Mathematics
Page: 178
View: 5299
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Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of applications of stochastic dynamic programming. The book begins with a chapter on various finite-stage models, illustrating the wide range of applications of stochastic dynamic programming. Subsequent chapters study infinite-stage models: discounting future returns, minimizing nonnegative costs, maximizing nonnegative returns, and maximizing the long-run average return. Each of these chapters first considers whether an optimal policy need exist—providing counterexamples where appropriate—and then presents methods for obtaining such policies when they do. In addition, general areas of application are presented. The final two chapters are concerned with more specialized models. These include stochastic scheduling models and a type of process known as a multiproject bandit. The mathematical prerequisites for this text are relatively few. No prior knowledge of dynamic programming is assumed and only a moderate familiarity with probability— including the use of conditional expectation—is necessary.

An Elementary Introduction to Mathematical Finance


Author: Sheldon M. Ross
Publisher: Cambridge University Press
ISBN: 1139498037
Category: Mathematics
Page: N.A
View: 2173
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This textbook on the basics of option pricing is accessible to readers with limited mathematical training. It is for both professional traders and undergraduates studying the basics of finance. Assuming no prior knowledge of probability, Sheldon M. Ross offers clear, simple explanations of arbitrage, the Black-Scholes option pricing formula, and other topics such as utility functions, optimal portfolio selections, and the capital assets pricing model. Among the many new features of this third edition are new chapters on Brownian motion and geometric Brownian motion, stochastic order relations and stochastic dynamic programming, along with expanded sets of exercises and references for all the chapters.

An Introduction to Probabilistic Modeling


Author: Pierre Bremaud
Publisher: Springer Science & Business Media
ISBN: 9780387964607
Category: Mathematics
Page: 207
View: 3091
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Introduction to the basic concepts of probability theory: independence, expectation, convergence in law and almost-sure convergence. Short expositions of more advanced topics such as Markov Chains, Stochastic Processes, Bayesian Decision Theory and Information Theory.

Simulation


Author: Sheldon M. Ross
Publisher: Academic Press
ISBN: 0124158250
Category: Computers
Page: 310
View: 4875
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"In formulating a stochastic model to describe a real phenomenon, it used to be that one compromised between choosing a model that is a realistic replica of the actual situation and choosing one whose mathematical analysis is tractable. That is, there did not seem to be any payoff in choosing a model that faithfully conformed to the phenomenon under study if it were not possible to mathematically analyze that model. Similar considerations have led to the concentration on asymptotic or steady-state results as opposed to the more useful ones on transient time. However, the relatively recent advent of fast and inexpensive computational power has opened up another approach--namely, to try to model the phenomenon as faithfully as possible and then to rely on a simulation study to analyze it"--

Probability Models for Computer Science


Author: Sheldon M. Ross
Publisher: Taylor & Francis US
ISBN: 9780125980517
Category: Computers
Page: 288
View: 363
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The role of probability in computer science has been growing for years and, in lieu of a tailored textbook, many courses have employed a variety of similar, but not entirely applicable, alternatives. To meet the needs of the computer science graduate student (and the advanced undergraduate), best-selling author Sheldon Ross has developed the premier probability text for aspiring computer scientists involved in computer simulation and modeling. The math is precise and easily understood. As with his other texts, Sheldon Ross presents very clear explanations of concepts and covers those probability models that are most in demand by, and applicable to, computer science and related majors and practitioners. Many interesting examples and exercises have been chosen to illuminate the techniques presented Examples relating to bin packing, sorting algorithms, the find algorithm, random graphs, self-organising list problems, the maximum weighted independent set problem, hashing, probabilistic verification, max SAT problem, queuing networks, distributed workload models, and many othersMany interesting examples and exercises have been chosen to illuminate the techniques presented