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Markov Processes

Clear, rigorous, and intuitive, Markov Processes provides a bridge from an undergraduate probability course to a course in stochastic;

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Markov Chains and Decision Processes for Engineers and Managers

service systems. However, most books on Markov chains or decision processes are often either highly theoretical, with few examples, or highly;

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Markov Chains and Decision Processes for Engineers and Managers

service systems. However, most books on Markov chains or decision processes are often either highly theoretical, with few examples, or highly;

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Markov Processes and Applications

illustrated in illuminating examples. This book will be extremely useful to anybody teaching a course on Markov processes. Jean-Francois Le Gall;

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Semi-Dirichlet Forms and Markov Processes

This book deals with analytic treatments of Markov processes. Symmetric Dirichlet forms and their associated Markov processes are important;

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Ergodic Behavior of Markov Processes

The general topic of this book is the ergodic behavior of Markov processes. A detailed introduction to methods for proving ergodicity and;

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Markov-modulated Processes And Semiregenerative Phenomena

The book presents a coherent treatment of Markov random walks and Markov additive processes together with their applications. Part I;

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Statistical Inference for Piecewise-deterministic Markov Processes

Piecewise-deterministic Markov processes form a class of stochastic models with a sizeable scope of applications: biology, insurance;

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Asymptotic Properties of Permanental Sequences

Markov chains. The authors study alpha-permanental processes that are positive infinitely divisible processes determined by the potential;

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Statistical Topics and Stochastic Models for Dependent Data with Applications

corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov;

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Markov Renewal and Piecewise Deterministic Processes

deterministic functions of CSMPs (Completed Semi-Markov Processes), i.e. semi-Markov processes completed to become Markov processes. This remark leads;

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Boundary Value Problems and Markov Processes: Functional Analysis Methods for Markov Processes

processes. It brings these three fields of analysis together, providing a comprehensive study of Markov processes from a broad perspective. The;

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Markov Processes and Potential Theory

This advanced text explores the relationship between Markov processes and potential theory, in addition to aspects of the theory;

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Semi-Markov Processes

Semi-Markov Processes: Applications in System Reliability and Maintenance is a modern view of discrete state space and continuous time;

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Competitive Markov Decision Processes

This book is intended as a text covering the central concepts and techniques of Competitive Markov Decision Processes. It is an attempt to;

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Competitive Markov Decision Processes

This book is intended as a text covering the central concepts and techniques of Competitive Markov Decision Processes. It is an attempt to;

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An Introduction to Markov Processes

Provides a more accessible introduction than other books on Markov processes by emphasizing the structure of the subject and avoiding;

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Finite Markov Processes and Their Applications

A self-contained treatment of finite Markov chains and processes, this text covers both theory and applications. Author Marius Iosifescu;

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Hidden Markov Processes

This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems;

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Markov Decision Processes

Examines several fundamentals concerning the manner in which Markov decision problems may be properly formulated and the determination;

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Multidimensional Diffusion Processes

From the reviews: This book is an excellent presentation of the application of martingale theory to the theory of Markov processes;

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First Look At Stochastic Processes, A

martingales. The final chapter provides a brief introduction to Brownian motion, Markov processes in continuous time and space, Poisson processes, and;

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First Look At Stochastic Processes, A

martingales. The final chapter provides a brief introduction to Brownian motion, Markov processes in continuous time and space, Poisson processes, and;

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Markov Processes for Stochastic Modeling

Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state;

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Markov Processes, Gaussian Processes, and Local Times

Written by two foremost researchers in the field, this book studies the local times of Markov processes by employing isomorphism theorems;

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Generated Dynamics of Markov and Quantum Processes

This book presents Markov and quantum processes as two sides of a coin called generated stochastic processes. It deals with quantum;

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Markov Processes

making them available to future generations of statisticians, mathematicians, and scientists. '[A]anyone who works with Markov processes whose;

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