plot.cvCovEst {cvCovEst}  R Documentation 
Generic Plot Method for cvCovEst
Description
The plot
method is a generic method for plotting objects
of class, "cvCovEst"
. The method is designed as a tool for diagnostic
and exploratory analysis purposes when selecting a covariance matrix
estimator using cvCovEst
.
Usage
## S3 method for class 'cvCovEst'
plot(
x,
dat_orig,
estimator = NULL,
plot_type = c("summary"),
stat = c("min"),
k = NULL,
leading = TRUE,
abs_v = TRUE,
switch_vars = FALSE,
min_max = FALSE,
...
)
Arguments
x 
An object of class, 
dat_orig 
The 
estimator 
A 
plot_type 
A 
stat 
A 
k 
A 
leading 
A 
abs_v 
A 
switch_vars 
A 
min_max 
A 
... 
Additional arguments passed to the plot method. These are not explicitly used and should be ignored by the user. 
Details
This plot method is designed to aide users in understanding the
estimation procedure carried out in cvCovEst()
. There are
currently four different values for plot_type
that can be called:

"eigen"
 Plots the eigenvalues associated with the specifiedestimator
andstat
arguments in decreasing order. 
"risk"
 Plots the crossvalidated risk of the specifiedestimator
as a function of the hyperparameter values passed tocvCovEst()
. This type of plot is only compatible with estimators which take hyperparameters as arguments. 
"heatmap"
 Plots a covariance heat map associated with the specifiedestimator
andstat
arguments. Multiple estimators and performance stats may be specified to produce grids of heat maps. 
"summary"
 Specifying this plot type will run all of the above plots for the best performing estimator selected bycvCovEst()
. These plots are then combined into a single panel along with a table containing the best performing estimator within each class. If the optimal estimator selected bycvCovEst()
does not have hyperparameters, then the risk plot is replaced with a table displaying the minimum, first quartile, median, third quartile, and maximum of the crossvalidated risk associated with each class of estimator.
The stat
argument accepts five values. They each correspond to a
summary statistic of the crossvalidated risk distribution within a class
of estimator. Possible values are:

"min"
 minimum 
"Q1"
 first quartile 
"median"
 median 
"Q3"
 third quartile 
"max"
 maximum
Value
A plot object
Examples
cv_dat < cvCovEst(
dat = mtcars,
estimators = c(
thresholdingEst, sampleCovEst
),
estimator_params = list(
thresholdingEst = list(gamma = seq(0.1, 0.9, 0.1))
)
)
plot(x = cv_dat, dat_orig = mtcars)