Bayesian Analysis of Stochastic Process Models

Beschreibung

Bayesian analysis of complex models based on stochastic processes has seen a surge in research activity in recent years. Bayesian Analysis of Stochastic Process Models provides a unified treatment of Bayesian analysis of models based on stochastic processes, covering the main classes of stochastic processing including modeling, computational, inference, forecasting, decision making and important applied models. Bayesian Analysis of Stochastic Process Models: * Explores Bayesian analysis of models based on stochastic processes, providing a unified treatment. * Provides a thorough introduction for research students. * Includes computational tools to deal with complex problems, illustrated with real life case studies * Computational tools to deal with complex problems are illustrated along with real life case studies * Examines inference, prediction and decision making. Researchers, graduate and advanced undergraduate students interested in stochastic processes in fields such as statistics, operations research (OR), engineering, finance, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practitioners of OR, stochastic modelling and applied statistics will also find this book useful.
Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified treatment of Bayesian analysis of models based on stochastic processes, covering the main classes of stochastic processing including modeling, computational, inference, forecasting, decision making and important applied models. Key features: * Explores Bayesian analysis of models based on stochastic processes, providing a unified treatment. * Provides a thorough introduction for research students. * Computational tools to deal with complex problems are illustrated along with real life case studies * Looks at inference, prediction and decision making. Researchers, graduate and advanced undergraduate students interested in stochastic processes in fields such as statistics, operations research (OR), engineering, finance, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practitioners of OR, stochastic modelling and applied statistics will also find this book useful.

Autor*in

David Insua

Themen in »Bayesian Analysis of Stochastic Process Models«

Bayesian Analysis Bayessches Verfahren Bayes-Verfahren Computational & Graphical Statistics Engineering Statistics Experimental Design Rechnergestützte u. graphische Statistik Statistics Statistik Statistik in den Ingenieurwissenschaften Versuchsplanung

Stimmen zu »Bayesian Analysis of Stochastic Process Models«

Details

Link teilen