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| Basic Notions | |
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| Sample Space and Events | |
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| Probabilities | |
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| Counting Techniques | |
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| Independence and Conditional Probability | |
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| Independence | |
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| Conditioning | |
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| The Borel-Cantelli Theorem | |
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| Discrete Random Variables | |
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| Random Variables and Vectors | |
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| Expected Value | |
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| Variance and Other Moments | |
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| Inequalities for Deviations | |
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| Some Basic Distributions | |
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| Convergence of Random Variables | |
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| The Law of Large Numbers | |
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| Conditional Expectation | |
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| Generating Functions | |
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| Branching Processes | |
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| Random Walk Revisited | |
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| Branching Processes | |
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| Generating Functions | |
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| Branching Processes Revisited | |
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| More on Random Walk | |
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| Markov Chains | |
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| Definitions and Examples | |
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| Probability Distributions of Markov Chains | |
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| The First Step Analysis | |
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| Passage Times | |
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| Variables Defined on a Markov Chain | |
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| Ergodicity and Stationary Distributions | |
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| A Classification of States and Ergodicity | |
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| Continuous Random Variables | |
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| Continuous Distributions | |
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| Some Basic Distributions | |
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| Continuous Multivariate Distributions | |
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| Sums of Independent Random Variables | |
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| Conditional Distributions and Expectations | |
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| Distributions in the General Case | |
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| Simulation | |
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| Distribution Functions | |
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| Expected Values | |
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| On Convergence in Distribution and Probability | |
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| Simulation | |
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| Histograms | |
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| Moment Generating Functions | |
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| Definitions and Properties | |
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| Some Examples of Applications | |
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| Exponential or Bernstein-Chernoff's Bounds | |
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| The Central Limit Theorem for Independent Random Variables | |
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| The Central Limit Theorem (CLT) for Independent and Identically Distributed Random Variables | |
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| The CLT for Independent Variables in the General Case | |
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| Covariance Analysis | |
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| The Multivariate Normal Distribution | |
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| The Multivariate Central Limit Theorem | |
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| Covariance and Correlation | |
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| Covariance Matrices and Some Applications | |
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| The Multivariate Normal Distribution | |
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| Maxima and Minima of Random Variables | |
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| Elements of Reliability Theory | |
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| Hazard Rate and Survival Probabilities | |
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| Maxima and Minima of Random Variables | |
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| Reliability Characteristics | |
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| Limit Theorems for Maxima and Minima | |
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| Hazard Rate | |
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| Survival Probabilities | |
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| Stochastic Processes: Preliminaries | |
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| A General Definition | |
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| Processes with Independent Increments | |
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| Brownian Motion | |
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| Markov Processes | |
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| A Representation and Simulation of Markov Processes in Discrete Time | |
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| Counting and Queuing Processes | |
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| Birth and Death Processes: A General Scheme | |
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| Poisson Processes | |
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| Birth and Death Processes | |
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| Elements of Renewal Theory | |
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| Preliminaries | |
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| Limit Theorems | |
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| Some Proofs | |
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| Martingales in Discrete Time | |
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| Definitions and Properties | |
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| Optional Time and Some Applications | |
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| Martingales and a Financial Market Model | |
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| Limit Theorems for Martingales | |
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| Brownian Motion and Martingales in Continuous Time | |
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| Brownian Motion and Its Generalizations | |
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| Martingales in Continuous Time | |
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| More on Dependency Structures | |
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| Arrangement Structures and the Corresponding Dependencies | |
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| Measures of Dependency | |
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| Limit Theorems for Dependent Random Variables | |
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| Symmetric Distributions | |
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| De Finetti's Theorem | |
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| Comparison of Random Variables | |
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| Risk Evaluation | |
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| Some Particular Criteria | |
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| Expected Utility | |
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| Generalizations of the EUM Criterion | |
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| Appendix | |
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| References | |
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| Answers to Exercises | |
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| Index | |
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| Exercises appear at the end of each chapter | |