Introduction to stochastic models

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1. Verfasser: Goodman, Roe 1938- (VerfasserIn)
Format: Buch
Sprache:English
Veröffentlicht: Menlo Park, Calif. Benjamin/Cummings 1988
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Datensatz im Suchindex

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adam_text Contents Chapter 1 Sample Spaces 1 Introduction 1 1.1 Experiments with Random Outcomes 1 1.2 Sample Spaces, Events, and Random Variables 3 Exercises 6 Chapter 2 Probabilities 7 Introduction 7 2.1 Relative Frequency of Events 7 2.2 Axioms of Probability 13 2.3 Conditional Probability and Bayes Formula 24 2.4 Stochastic Independence 29 2.5 Repeated Independent Trials 32 Exercises 40 Chapter 3 Distributions and Expectations of Random Variables 45 Introduction 45 3.1 Distribution Function of a Random Variable 45 3.2 Discrete Random Variables 47 3.3 Continuous Random Variables 52 3.4 Expectation of a Random Variable 57 ix Contents 3.5 Functions of a Random Variable 61 3.6 Simulation of a Random Variable 66 Exercises 71 Chapter 4 Joint Distributions of Random Variables 75 Introduction 75 4.1 Joint Mass Functions and Densities 75 4.2 Independent Random Variables 82 4.3 Moment generating Functions 89 4.4 Families of Random Variables 92 4.5 Markov and Chebyshev Inequalities 95 4.6 Law of Large Numbers 98 4.7 Central Limit Theorem 102 Exercises 108 Chapter 5 Conditional Expectations 113 Introduction 113 5.1 Conditional Distributions (Discrete Case) 113 5.2 Conditional Expectations 115 5.3 Conditional Expectations (Continuous Case) 118 5.4 Sum of a Random Number of Random Variables 122 Exercises 124 Chapter 6 Markov Chains 127 Introduction 127 6.1 State Spaces and Transition Diagrams 127 6.2 Joint Probabilities 133 6.3 More Examples 139 6.4 « Step Transition Probabilities 146 6.5 Classification of States 151 6.6 Absorbing Chains 157 6.7 Regular Chains 164 6.8 Stationary Distributions 169 6.9 Time Averages 172 6.10 Sojourn Times and First Entrance Times 176 Exercises 182 Contents Chapter 7 The Poisson Process 187 Introduction 187 7.1 Memoryless Random Variables 187 7.2 Replacement Models 193 7.3 Simulation of a Poisson Process 194 7.4 Fundamental Properties of a Poisson Process 196 7.5 Differential Equations for a Poisson Process 200 Exercises 203 Chapter 8 Continuous Time Stochastic Processes 207 Introduction 207 8.1 Stochastic Processes 207 8.2 Characterization of the Poisson Process 209 8.3 Discrete Time Approximation to the Poisson Process 213 8.4 Compound Poisson Process 215 8.5 Nonhomogeneous Poisson Process 218 8.6 Queueing Processes 221 8.7 M/M/l Queue and Exponential Models 224 Exercises 227 Chapter 9 Birth and Death Processes 231 Introduction 231 9.1 Linear Growth Model 231 9.2 Birth Death Processes 232 9.3 State Transition Diagrams 234 9.4 Transition Probabilities 237 9.5 Differential Equations for Transition Probabilities 241 9.6 Pure Birth Processes 245 Exercises 247 Chapter 10 Steady State Probabilities 251 Introduction 251 10.1 Approach to Equilibrium 251 10.2 Steady State Equations 252 10.3 Limiting Probabilities 254 10.4 Balance Equations 258 Contents 10.5 Time Averages 260 10.6 Steady State Analysis of the M/M/l Queue 264 10.7 Machine Repair Model 266 Exercises 267 Chapter 11 General Queueing Systems 271 Introduction 271 11.1 Long Term Average Queue Characteristics 272 11.2 Little s Formula 274 11.3 Steady State Behavior of M/M/l Queue 275 11.4 Service in Stages 278 11.5 Jackson s Theorem 282 11.6 M/M/s Queue Statistics 284 11.7 Optimization Problems 291 11.8 Examples of Queue Simulation 296 Exercises 305 Chapter 12 Renewal Processes 313 Introduction 313 12.1 Failure Rates 314 12.2 Renewal Model 317 12.3 Random Stopping Rules and Wald s Identity 321 12.4 Renewals with Rewards 324 12.5 Age Replacement Model 328 12.6 Regeneration Points 332 12.7 Lifetime Sampling and the Inspection Paradox 338 12.8 Waiting Times for the M/G/l Queue 343 Exercises 346 Table 1. Discrete Probability Distributions 352 Table 2. Continuous Probability Distributions 353 Table 3. Cumulative Normal Distribution Function 354 Table 4. Random Numbers 355 Suggestions for Further Reading 356 Numerical Solutions to Selected Exercises 358 Index 364
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physical XII, 368 S. graph. Darst.
publishDate 1988
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record_format marc
spellingShingle Goodman, Roe 1938-
Introduction to stochastic models
Probabilités
Processus stochastiques - Modèles mathématiques
Mathematisches Modell
Probabilities
Stochastic processes Mathematical models
Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd
Stochastischer Prozess (DE-588)4057630-9 gnd
Stochastisches Modell (DE-588)4057633-4 gnd
subject_GND (DE-588)4064324-4
(DE-588)4057630-9
(DE-588)4057633-4
(DE-588)4123623-3
title Introduction to stochastic models
title_auth Introduction to stochastic models
title_exact_search Introduction to stochastic models
title_full Introduction to stochastic models
title_fullStr Introduction to stochastic models
title_full_unstemmed Introduction to stochastic models
title_short Introduction to stochastic models
title_sort introduction to stochastic models
topic Probabilités
Processus stochastiques - Modèles mathématiques
Mathematisches Modell
Probabilities
Stochastic processes Mathematical models
Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd
Stochastischer Prozess (DE-588)4057630-9 gnd
Stochastisches Modell (DE-588)4057633-4 gnd
topic_facet Probabilités
Processus stochastiques - Modèles mathématiques
Mathematisches Modell
Probabilities
Stochastic processes Mathematical models
Wahrscheinlichkeitsrechnung
Stochastischer Prozess
Stochastisches Modell
Lehrbuch
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