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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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Semi-Dirichlet Forms and Markov Processes

wide class of Markov processes and analytic theory which do not possess the dual Markov processes. In particular, under the semi-Dirichlet form;

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Introduction to Hidden Semi-Markov Models

to the subject by first developing the theory of Markov processes in an elementary discrete time, finite state framework suitable for senior;

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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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Random Motions in Markov and SemiMarkov Random Environments 2

part contains applications of Markov and semi-Markov motions in mathematical finance. It includes applications of telegraph processes;

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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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Stochastic Systems In Merging Phase Space

integral functionals, increment processes and impulsive processes. All these systems are switched by Markov and semi-Markov processes whose phase;

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Asymptotic Analyses for Complex Evolutionary Systems with Markov and Semi-Markov Switching Using Approximation Schemes

This book analyzes stochastic evolutionary models under the impulse of diffusion, as well as Markov and semi-Markov switches. Models are;

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Modern Trends in Controlled Stochastic Processes:

methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information;

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New Computational Methods in Power System Reliability

simulation and with random processes methods, Semi-Markov and Markov reward models and genetic algorithm. The book can be considered as complementary;

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New Computational Methods in Power System Reliability

simulation and with random processes methods, Semi-Markov and Markov reward models and genetic algorithm. The book can be considered as complementary;

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Introduction to Stochastic Models

as physics, engineering, biology and genetics, economics and social sciences. It covers Markov and semi-Markov models, as well as their;

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Basic Stochastic Processes

This book presents basic stochastic processes, stochastic calculus including Levy processes on one hand, and Markov and Semi Markov models;

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Modeling, Analysis, Design and Control of Stochastic Systems

, cumulative processes and semi-Markov processes. All the material is illustrated with many examples, and the book emphasises numerical answers to the;

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Demography and Health Issues

book describes diverse stochastic processes as well as Markov and semi-Markov models in demography and population studies, along with chapters;

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Random Motions in Markov and SemiMarkov Random Environments 1

This book is the first of two volumes on random motions in Markov and semi-Markov random environments. This first volume focuses on;

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An Introduction to Stochastic Processes

and continuous-time Markov chains, Markov renewal and semi-regenerative processes, and Brownian motion and other diffusion processes. Each;

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Switching Processes in Queueing Models

models which covers models in a Markov or semi-Markov environment, models under the influence of flows of external or internal perturbations;

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Applied Probability Models with Optimization Applications

renewal theory and Markov chains; semi-Markov, Markov renewal, and regenerative processes; inventory theory; and Brownian motion and continuous;

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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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Semi-Markov Models

Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes;

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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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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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