mixed3000

<p>mixed3000 is a simulated dataset for illustration our p_learning alogorithm.</p>

datasets

Provides an equivalent measure of partial correlation coefficients for high-dimensional Gaussian Graphical Models to learn and visualize the underlying relationships between variables from single or multiple datasets. You can refer to Liang, F., Song, Q. and Qiu, P. (2015) <doi:10.1080/01621459.2015.1012391> for more detail. Based on this method, the package also provides the method for constructing networks for Next Generation Sequencing Data, for jointly estimating multiple Gaussian Graphical Models and constructing directed acyclic graph (Bayesian Network).

Bochao Jia

equSA

Estimate Directed and Undirected Graphical Models and Construct
Networks

mixed3000 function

<p>mixed3000 dataset is a 3000x100 matrix. Each row represents a observation and each column represents a variable. It contains 50 continuous variables and 50 binary variables.</p>

mixed3000: One example dataset for p_learning

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