bandingEst() and
taperingEst() documentation.cvRiskPlot() and matrixMetrics().cvCovEst() no longer accepts center and
scale arguments. Data centering is now handled within each
estimator function. Users no longer have an option to scale their data.
If they’d like to produce a correlation matrix, they must scale the
cvCovEst() estimate using cov2cor()..data$ in dplyr::select() statements.spikedOperatorShrinkEst(),
spikedFrobeniusShrinkEst() and
spikedSteinShrinkEst(), and apply the asymptotically
optimal amount of shrinkage on the sample covariance matrix’s
eigenvalues with respect to their respective loss functions. For more
information on these estimators, see Donoho et al.’s Annals of
Statistics article “Optimal Shrinkage of Eigenvalues in the Spiked
Covariance Model”.summary() now reports metrics about the candidate
estimators’ estimates, like their condition numbers, signe, and sparsity
levels.scadEst() and adaptiveLassoEst() are now
vectorized, greatly improving their computational efficiency. Thanks,
Brian!cvCovEst() no longer accepts the
true_cov_mat argument.cvCovEst is now ready for publication through
JOSS.inst/REFERENCES.bibpkgdown documentationcvCovEst(). This is the last version of
cvCovEst that can be used to reproduce the simulation
results of the accompanying manuscript, “Cross-Validated Loss-Based
Covariance Matrix Estimator Selection in High Dimensions”.summary.cvCovEst() when a single summary
function is specified now immediately returns a table instead of a list
of length 1 that contains said table.summary.cvCovEst() no longer have
dplyr groups.empirical_risk column in risk_df
table output by cvCovEst() to cv_risk.robustPoetEst() warning again its use
for correlation matrix estimation.robustPoetEst plots.cvCovEst R package a public repository
GitHub.cvCovEst now possesses a slew of diagnostic and
visualization tools. A detailed description of these functions will be
added to the vignette in the near future.NEWS.md, adding consistency in bullet point
indicator and enforcing the 80-column rule.stringi
since only invoked in a single pipe call in checkArgs.cvMatrixFrobeniusLoss the default loss
function.cvScaledMatrixFrobeniusLoss, a new matrix-based
loss function that scales squared error calculations associated with
each entry of a covariance matrix estimate by the sample variances of
the entry’s row and column variables. This is particularly useful if the
features of your dataset are of different magnitude. It’s approximately
equivalent to estimating the correlation matrix, but without the need to
re-scale the estimated correlation matrix to be an estimated covariance
matrix.denseLinearShrinkEst: the shrinkage
parameter was often selected such that the dense target was returned as
the estimate.robustPoetEst has been added to the library of
candidate estimators.nlShrinkLWEst by
changing a conditional, as per
https://github.com/PhilBoileau/cvCovEst/issues/23.tidyverse code
style via the first call to styler in this codebase
(via make style).NEWS.md.stats::cov with coop::covar
after resolving the issue on Linux machines, as per
https://github.com/PhilBoileau/cvCovEst/issues/18.cvCovEst and from cvFrobeniusLoss when the
true covariance matrix is passed in.coop::covar due to strange parallelization
issue on Linux machines. Hopefully we can use it again one day.cvCovEst if the estimator in questions doesn’t have any
hyperparameters.cvCovEst.cvCovEst function.origami.Roxygen
styling.NEWS.md file to track changes to the
package.
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