Bayesian Analysis of Non-Stationary Gaussian Process Models
Enables off-the-shelf functionality for fully Bayesian, nonstationary Gaussian process modeling. The approach to nonstationary modeling involves a closed-form, convolution-based covariance function with spatially-varying parameters; these parameter processes can be specified either deterministically (using covariates or basis functions) or stochastically (using approximate Gaussian processes). Stationary Gaussian processes are a special case of our methodology, and we furthermore implement approximate Gaussian process inference to account for very large spatial data sets (Finley, et al (2017) <arXiv:1702.00434v2>). Bayesian inference is carried out using Markov chain Monte Carlo methods via the 'nimble' package, and posterior prediction for the Gaussian process at unobserved locations is provided as a post-processing step.

Han Yu, Janhavi Moharil, Rachael Hageman Blair
Rgraphviz, gRbase, igraph, RColorBrewer, fields, doBy, qtlnet,
methods, qtl, graph
Belief propagation methods in Bayesian Networks to propagate evidence through the network. The implementation of these methods are based on the article: Cowell, RG (2005). Local Propagation in Conditional Gaussian Bayesian Networks <http://www.jmlr.org/papers/volume6/cowell05a/>.

Rgraphviz, gRbase, igraph, RColorBrewer, fields, doBy, qtlnet,
methods, qtl, graph, bnlearn

Rgraphviz, igraph, RColorBrewer, fields, doBy, qtlnet,
methods, qtl, graph, bnlearn

Han Yu, Rachael Blair, Janhavi Moharil, Andrew Yan
igraph, RColorBrewer, fields, doBy, methods, qtl, graph,
bnlearn, graphics, qtlnet
Belief propagation methods in Bayesian Networks to propagate evidence through the network. The implementation of these methods are based on the article: Cowell, RG (2005). Local Propagation in Conditional Gaussian Bayesian Networks <http://www.jmlr.org/papers/volume6/cowell05a/>. The optional 'cyjShiny' package for running the Shiny app is available at <https://github.com/cytoscape/cyjShiny>. Please see the example in the documentation of 'runBayesNetApp' function for installing 'cyjShiny' package from GitHub.