Description: Allows spatial implementation of Bayesian networks and mapping in geographical space. It makes maps of expected value (or most likely state) given known and unknown conditions, maps of uncertainty measured as coefficient of variation or Shannon index (entropy), maps of probability associated to any states of any node of the network. Some additional features are provided as well: parallel processing options, data discretization routines and function wrappers designed for users with minimal knowledge of the R language. Outputs can be exported to any common GIS format. Development was funded by the European Union FP7 (2007-2013), under project ROBIN (<http://robinproject.info>).

Imports: raster, rgdal, gRbase, gRain, doParallel, foreach

Copyright: Centre for Ecology and Hydrology - CEH
Imports: raster, rgdal, sf, gRbase, gRain, doParallel, foreach, utils
Description: Allows spatial implementation of Bayesian networks and mapping in geographical space. It makes maps of expected value (or most likely state) given known and unknown conditions, maps of uncertainty measured as coefficient of variation or Shannon index (entropy), maps of probability associated to any states of any node of the network. Some additional features are provided as well: parallel processing options, data discretization routines and function wrappers designed for users with minimal knowledge of the R language. Outputs can be exported to any common GIS format.

Description: Bayesian Network Structure Learning from Data with Missing Values.
The package implements the Silander-Myllymaki complete search,
the Max-Min Parents-and-Children, the Hill-Climbing, the
Max-Min Hill-climbing heuristic searches, and the Structural
Expectation-Maximization algorithm. Available scoring functions are
BDeu, AIC, BIC. The package also implements methods for generating and using
bootstrap samples, imputed data, inference.
Title: Bayesian Network Structure Learning from Data with Missing
Depends: R (>= 2.10), bitops, Matrix, igraph, methods
Suggests: graph, Rgraphviz, knitr, testthat
Authors@R: c(person("Francesco", "Sambo", role=c("aut","cre"), email="francesco.sambo@unipd.it"),