pcalg (version 2.7-12)

gmG: Graphical Model 8-Dimensional Gaussian Example Data

Description

These two data sets contain a matrix containing information on eight gaussian variables and the corresonding DAG model.

Usage

data(gmG)

Format

gmG and gmG8 are each a list of two components

x:

a numeric matrix \(5000 \times 8\).

g:

a graph, i.e., of formal class "graphNEL" from package graph with 6 slots
.. ..@ nodes : chr [1:8] "1" "2" "3" "4" ...
.. ..@ edgeL :List of 8
........

Details

The data was generated as indicated below. First, a random DAG model was generated, then 5000 samples were drawn from “almost” this model, for gmG: In the previous version, the data generation wgtMatrix had the non-zero weights in reversed order for each node. On the other hand, for gmG8, the correct weights were used in all cases

Examples

data(gmG)
str(gmG, max=3)
stopifnot(identical(gmG $ g, gmG8 $ g))
if(dev.interactive()) { ## to save time in tests
  round(as(gmG $ g, "Matrix"), 2) # weight ("adjacency") matrix
  if (require(Rgraphviz)) plot(gmG$g)
  pairs(gmG$x, gap = 0,
	panel=function(...) smoothScatter(..., add=TRUE))
}