Bayesian Networks
Bayesian Networks: With Examples in R, Second Edition introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples illustrate each step of the modelling process and discuss…
Specifikacia Bayesian Networks
Bayesian Networks: With Examples in R, Second Edition introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples illustrate each step of the modelling process and discuss side by side the underlying theory and its application using R code. The examples start from the simplest notions and gradually increase in complexity. In particular, this new edition contains significant new material on topics from modern machine-learning practice: dynamic networks, networks with heterogeneous variables, and model validation.The first three chapters explain the whole process of Bayesian network modelling, from structure learning to parameter learning to inference. These chapters cover discrete, Gaussian, and conditional Gaussian Bayesian networks. The following two chapters delve into dynamic networks (to model temporal data) and into networks
Bayesian Networks
Bayesian Models
Bayesian Econometric Methods
Applied Bayesian Statistics
Bayesian Essentials with R
Bayesian Thinking in Biostatistics
Bayesian Computation with R
Bayesian Econometrics Koop Gary
Computer Networks
Delinquent Networks
Bayesian Methods in Statistics
Strange Networks
Bayesian Data Analysis Gelman Andrew