Nothing
summary.lambdaSelection <- function(object, ...){
x <- object
# stop if the object is not a pcorSimJoint object.
if (!inherits(x, "lambdaSelection"))
stop("use only with \"lambdaSelection\" object")
if(length(x$criterion)==2)
cat(gettextf("\n \t lambda selection by optimizing %s / %s risk function", x$criterion[1], x$criterion[2]),"\n\n")
else
{
if(x$criterion == "A-MSE")
{
callit <- attr(x, "generator")
cat(gettextf("\n \t lambda selection by optimizing %s risk function with %s generator ", x$criterion, callit),"\n\n")
}
else
cat(gettextf("\n \t lambda selection by optimizing %s risk function", x$criterion),"\n\n")
}
P <- dim(attr(x, "bestpath"))[1]
if(length(x$criterion)==2)
{
SP1 <- sum(attr(x, "bestpath"))/(P*(P-1))
SP2 <- sum(attr(x, "bestpath2"))/(P*(P-1))
cat(gettextf("optimal lambda = %s, \t Sparsity graph structure = %s", round(x$opt.lambda[1],4), round(1-SP1,4)), "\n\n")
cat(gettextf("optimal lambda = %s, \t Sparsity graph structure = %s", round(x$opt.lambda[2],4), round(1-SP2,4)), "\n\n")
}
else{
SP <- sum(attr(x, "bestpath"))/(P*(P-1))
cat(gettextf("optimal lambda = %s, \t Sparsity graph structure = %s", round(x$opt.lambda[1],4), round(1-SP1,4)), "\n\n")
}
}
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