Электронная книга: David Insua «Bayesian Analysis of Stochastic Process Models»

Bayesian Analysis of Stochastic Process Models

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.

Издательство: "John Wiley&Sons Limited"

ISBN: 9780470975923

электронная книга

Купить за 8953.17 руб и скачать на Litres

Look at other dictionaries:

  • Bayesian network — A Bayesian network, Bayes network, belief network or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). For example …   Wikipedia

  • Dirichlet process — In probability theory, a Dirichlet process is a stochastic process that can be thought of as a probability distribution whose domain is itself a random distribution. That is, given a Dirichlet process , where H (the base distribution) is an… …   Wikipedia

  • Sensitivity analysis — (SA) is the study of how the variation (uncertainty) in the output of a mathematical model can be apportioned, qualitatively or quantitatively, to different sources of variation in the input of a model Saltelli, A., Ratto, M., Andres, T.,… …   Wikipedia

  • Niche apportionment models — Mechanistic models for niche apportionment are biological models used to explain relative species abundance distributions. These models describe how species break up resource pool in multi dimensional space, determining the distribution of… …   Wikipedia

  • Dynamic stochastic general equilibrium — modeling (abbreviated DSGE or sometimes SDGE or DGE) is a branch of applied general equilibrium theory that is influential in contemporary macroeconomics. The DSGE methodology attempts to explain aggregate economic phenomena, such as economic… …   Wikipedia

  • Gibbs sampling — In statistics and in statistical physics, Gibbs sampling or a Gibbs sampler is an algorithm to generate a sequence of samples from the joint probability distribution of two or more random variables. The purpose of such a sequence is to… …   Wikipedia

  • Neural network — For other uses, see Neural network (disambiguation). Simplified view of a feedforward artificial neural network The term neural network was traditionally used to refer to a network or circuit of biological neurons.[1] The modern usage of the term …   Wikipedia

  • Optimal design — This article is about the topic in the design of experiments. For the topic in optimal control theory, see shape optimization. Gustav Elfving developed the optimal design of experiments, and so minimized surveyors need for theodolite measurements …   Wikipedia

  • Maximum parsimony (phylogenetics) — Parsimony is a non parametric statistical method commonly used in computational phylogenetics for estimating phylogenies. Under parsimony, the preferred phylogenetic tree is the tree that requires the least evolutionary change to explain some… …   Wikipedia

  • Maximum parsimony — Maximum parsimony, often simply referred to as parsimony, is a non parametric statistical method commonly used in computational phylogenetics for estimating phylogenies. Under maximum parsimony, the preferred phylogenetic tree is the tree that… …   Wikipedia

  • Monte Carlo method — Not to be confused with Monte Carlo algorithm. Computational physics …   Wikipedia