Class "pcAlgo" of PC Algorithm Results, incl. Skeleton
## S4 method for signature 'pcAlgo,ANY' plot(x, y, main = NULL, zvalue.lwd = FALSE, lwd.max = 7, labels = NULL, ...) ## S3 method for class 'pcAlgo' print(x, amat = FALSE, zero.print = ".", ...) ## S4 method for signature 'pcAlgo' summary(object, amat = TRUE, zero.print = ".", ...) ## S4 method for signature 'pcAlgo' show(object)
x, object |
a |
y |
(generic |
main |
main title for the plot (with an automatic default). |
zvalue.lwd |
|
lwd.max |
maximal |
labels |
if non- |
amat |
|
zero.print |
string for printing |
... |
optional further arguments (passed from and to methods). |
The slots call
, n
, max.ord
, n.edgetests
,
sepset
, and pMax
are inherited from class
"gAlgo"
, see there.
In addition, "pcAlgo"
has slots
graph
:Object of class "graph"
:
the undirected or partially directed graph that was estimated.
zMin
:Deprecated.
Class "gAlgo"
.
signature(x = "pcAlgo")
: Plot the resulting
graph. If argument "zvalue.lwd"
is true, the
linewidth an edge reflects zMin
, so that
thicker lines indicate more reliable dependencies. The argument
"lwd.max"
controls the maximum linewidth.
signature(object = "pcAlgo")
: Show basic properties of
the fitted object
signature(object = "pcAlgo")
: Show details of
the fitted object
Markus Kalisch and Martin Maechler
showClass("pcAlgo") ## generate a pcAlgo object p <- 8 set.seed(45) myDAG <- randomDAG(p, prob = 0.3) n <- 10000 d.mat <- rmvDAG(n, myDAG, errDist = "normal") suffStat <- list(C = cor(d.mat), n = n) pc.fit <- pc(suffStat, indepTest = gaussCItest, alpha = 0.01, p = p) ## use methods of class pcAlgo show(pc.fit) if(require(Rgraphviz)) plot(pc.fit, main = "Fitted graph") summary(pc.fit) ## access slots of this object (g <- pc.fit@graph) str(ss <- pc.fit@sepset, max=1)
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