"monomvn"-class object## S3 method for class 'monomvn':
summary(object, Si = FALSE, ...)
## S3 method for class 'summary.monomvn':
print(x, ...)
## S3 method for class 'summary.monomvn':
plot(x, gt0 = FALSE, main = NULL,
xlab = "number of zeros", ...)"monomvn"-class object for that must be named
object for the generic methods summary.monomvn"monomvn"-class object that must be named x
for the generic printing and plotting methods
print.summary.monomvn and
object$S should be
inverted within top look for zeros within
summary.monomvn, indicating pairwise independence;
default is FALSEplot.summary.monomvn should exclude columns
of object$S or Si without any zero entriesplot.summary.monomvnplot.summary.monomvnprint.monomvn, or
plot.defaultsummary.monomvn returns a "summary.monomvn"-class
object, which is a list containing (a subset of) the items below. The other
functions do not return values."monomvn"-class objectmarg{ the proportion of zeros in object$S }object$SSi = TRUE this field contains the
proportion of zeros in the inverse of object$SSi = TRUE this field contains a
vector with the number of zeros in each column of the inverse
of object$Sprint.monomvn prints the call followed by a
summary of the regression method used at each iteration of the
algorithm, also indicating how many completely observed features
(columns) there were in the data.
For non-least-squares regressions (i.e., lm.ridge methods)
and indication of the method used for selecting the
number of components (i.e., CV, LOO, etc., or
none) is provided summary.monomvn summarizes information about the
number of zeros in the estimated covariance matrix object$S
and its inverse.
print.summary.monomvn calls print.monomvn
on the object and then prints the result of
summary.monomvn
plot.summary.monomvn makes histograms of the number of
zeros in the columns of object$S and its inverse
monomvn