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Semi-Markov Processes: Applications in System Reliability and Maintenance is a modern view of discrete state space and continuous time;
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undergraduates and graduates. The authors then introduce semi-Markov chains and hidden semi-Markov chains, before developing related estimation and;
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corresponding applications. The main classes of stochastic processes for dependent data investigated throughout this book are Markov, semi-Markov;
Vergelijkbare producten zoals Statistical Topics and Stochastic Models for Dependent Data with Applications
Featuring previously unpublished results, Semi-Markov Models: Control of Restorable Systems with Latent Failures describes;
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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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Hidden semi-Markov models (HSMMs) are among the most important models in the area of artificial intelligence / machine learning. Since;
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This book analyzes stochastic evolutionary models under the impulse of diffusion, as well as Markov and semi-Markov switches. Models are;
Vergelijkbare producten zoals Asymptotic Analyses for Complex Evolutionary Systems with Markov and Semi-Markov Switching Using Approximation Schemes
This book is the second of two volumes on random motions in Markov and semi-Markov random environments. This second volume focuses on high;
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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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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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, cumulative processes and semi-Markov processes. All the material is illustrated with many examples, and the book emphasises numerical answers to the;
Vergelijkbare producten zoals Modeling, Analysis, Design and Control of Stochastic Systems
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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simulation and with random processes methods, Semi-Markov and Markov reward models and genetic algorithm. The book can be considered as complementary;
Vergelijkbare producten zoals 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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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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HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process New case studies on animal;
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Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models;
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techniques, change point detection techniques on seismicity models, and, finally, semi-Markov models for earthquake forecasting.;
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. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions;
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Inference for Hidden Markov Models and related Models is een boek van Cuvillier Verlag;
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to the different problems presented in the book. Advanced topics such as nonlinear problems, Levy processes and semi-Markov models;
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integral functionals, increment processes and impulsive processes. All these systems are switched by Markov and semi-Markov processes whose phase;
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Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and;
Vergelijkbare producten zoals Markov Chains and Decision Processes for Engineers and Managers
Recognized as a powerful tool for dealing with uncertainty, Markov modeling can enhance your ability to analyze complex production and;
Vergelijkbare producten zoals Markov Chains and Decision Processes for Engineers and Managers
This book presents basic stochastic processes, stochastic calculus including Levy processes on one hand, and Markov and Semi Markov models;
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This book discusses mixture and hidden Markov models for modeling behavioral data. Mixture and hidden Markov models are statistical models;
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Drawing on the authors' extensive research in the analysis of categorical longitudinal data, Latent Markov Models for Longitudinal Data;
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