naive.getug.norm {lcd} | R Documentation |
Learns an undirected independence graph from a given data set. The data are assumed to be normally distributed.
naive.getug.norm(data, p.value)
data |
a data matrix with rows corresponding to observations and columns corresponding to random variables. |
p.value |
the thresholding p-value for each conditional independence test. |
For each pair of random variables, the function performs a conditional independence using the partial correlation coefficient. If the p-value of the test is smaller than the given threshold, then there will be an edge on the output graph. The function essentially uses the global Markov property of the undirected graph.
The adjacency matrix of the computed undirected graph, with dimnames the corresponding random variables.
Zongming Ma and Xiangrui Meng
Lauritzen, S. L. (1996). Graphical Models. Clarendon Press, Oxford.