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.
*...
Cuprins
Preface
PART ONE BASIC CONCEPTS AND TOOLS
1 Stochastic Processes 11
1.1 Introduction 11
1.2 Key Concepts in Stochastic Processes 11
1.3 Main Classes of Stochastic Proce...
Despre autor
Fabrizio Ruggeri, Research Director, CNR IMATI, Milano, Italy.
Michael P. Wiper, Associate Professor in Statistics, Department of Statistics, Universidad Carlos III de...