"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 that must be named
object for the generic methods summary.monomvn"monomvn"-class object that must be named x
for generic printing and plotting via
print.summary.monomvn and
object$S should be
inverted and inspected for zeros within
summary.monomvn, indicating pairwise independence;
default is FALSEplot.summary.monomvn should exclude columns
of object$S or Si without any zero entriesplot.summary.monomvnplot.summary.monomvn; otherwise default
automatically-generated text is usedprint.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 objectobject$Sobject$SSi = TRUE this field contains the
proportion of zeros in the inverse of object$SSi = TRUE this field contains a
vector with the number of zeros in each column of the inverse
of object$Smonomvn
and bmonomvn. print.monomvn prints the call followed by a
summary of the regression method used at each iteration of the
algorithm. It also indicates 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
bmonomvn, monomvn,
plot.monomvn