These two data sets contain a matrix containing information on eight gaussian variables and the corresonding DAG model.
data(gmG)
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 use in all cases
# NOT RUN {
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
plot(gmG $ g)
pairs(gmG$x, gap = 0,
panel=function(...) smoothScatter(..., add=TRUE))
}
# }
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