Version 2.2.8
Documentation:
- Provided package anchors for all Rd targets to other packages.
Version 2.2.7
Adjustments:
- Functions optPenaltyPchordal, ridgePchordal, ridgePsign, and
support4ridgeP (temporarily) deprecated (for major adjustments)
- Replaced if() conditions comparing class() to string with
evaluations using inherits()
Documentation:
Version 2.2.6
Documentation:
- Canonicalization of URLs.
- Update of published papers
Version 2.2.5
Documentation:
- Improved documentation and added new pkgdown
documentation website.
- NEWS file moved to markdown format instead of .Rd and available on
the website
Version 2.2.4
Adjustments:
- Documentation roxygenized.
- More selective importing and exporting.
- S3 implementation of ridgePoutput.
Version 2.2.3
Documentation:
- Updated CITATIONfile
- Updated READMEfile
Bug fixes:
- Fixed bug in GGMpathStats: Incorrectly stated before
that all igraph layouts were supported. Now they indeed are
supported.
Adjustments:
- Bioconductor dependencies are now automatically installed upon first
installation of rags2ridges.
- GGMpathStatsnow has additional visualization options:
It can handle all layout functions supported by igraph. Moreover, it is
now possible to specify custom coordinates for node-placement.
Version 2.2.2
Notifications:
- Hot fix due to class changes in “matrix”. No major visible user
changes.
- CNplotfunction again updated: higher max. iterations
for Lanczos method
Version 2.2.1
Notifications:
- Hot fix due to new RNG. No visible user changes.
Version 2.2
Notifications:
- optPenalty.LOOCVis deprecated. Please use- optPenalty.kCVinstead
- optPenalty.LOOCVautois deprecated. Please use- optPenalty.kCVautoinstead
Version 2.1.1
Documentation:
- Updated CITATIONfile
- Updated READMEfile
Adjustments:
- sparsifynow has an additional thresholding option:
‘connected’
Version 2.1
Documentation:
- Updated CITATIONfile
- Updated READMEfile
Bug fixes:
- Fixed bug in Ugraph:
- Incorrectly stated before that all igraph layouts were
supported.
- Now they indeed are supported.
 
Notifications:
- conditionNumberPlotis deprecated. Please use- CNplotinstead
- Features of the CNplotfunction (above and beyondconditionNumberPlot):
- The digitLossandrlDistarguments have
been removed
- These arguments have been replaced with the logical argument
Iaids
- Iaids = TRUEamends the basic condition number plot
with interpretational aids
- These aids are the approximate loss in digits of accuracy and and
approximation of the acceleration along the regularization path of the
condition number
- Argument mainis now a character argument
- Argument valuenow by default takes the value 1e-100
(convenient)
- Now uses C++ functionalty for additional speed
 
Adjustments:
- edgeHeatnow has aligned x-axis labels
- The visualizations of the optPenalty.LOOCVandoptPenalty.aLOOCVfunctions now will no longer produce
horizontal and/or vertical lines that fall outside the boundaries of the
figure
- optPenalty.LOOCVnow uses log-equidistant penalty grid
for optimal penalty parameter determination (this also enhances the
visualization)
- New features updated optPenalty.aLOOCVfunction:
- Function has been sped up by killing redundant inversion
- now uses log-equidistant penalty grid for optimal penalty parameter
determination (this also enhances the visualization)
 
- New features updated Ugraphfunction:
- One can now also specify vertex placement by coordinate
specification
- Now outputs, for convenience, the vertex coordinates of the plotted
graph
 
- ridgePathShas been sped up by killing redundant
inversion
- The covMLfunction has been amended with an argument
that indicates if a correlation matrix (instead of an ML estimate of a
covariance matrix) is desired. This offers more flexibility. One can now
get the ML estimate of the covariance matrix, the ML estimate of the
covariance matrix on standardized data, as well as the correlation
matrix
- The optPenalty.LOOCVautofunction has been amended with
an argument that indicates if the evaluation of the LOOCV score should
be performed on the correlation scale
- The optPenalty.LOOCVfunction has been amended with an
argument that indicates if the evaluation of the LOOCV score should be
performed on the correlation scale
- The optPenalty.aLOOCVfunction has been amended with an
argument that indicates if the evaluation of the approximate LOOCV score
should be performed on the correlation scale
Version 2.0
Documentation:
- Added this NEWSfile!
- Updated (and corrected) CITATIONfile
- Added READMEfile
- Added (selective) import statements for default packages as required
for R-devel
Additions:
- rags2ridges
now uses Rcpp and
RcppArmadillo
with core functions written in C++. The package should now
be at least two orders of magnitude faster in most cases.
- Added, next to the core module, the fused ridge module. The fused
module provides functionality for the estimation and graphical modeling
of multiple precision matrices from multiple high-dimensional data
classes. Functions from this module are generally suffixed with
.fused. Functions tied to (or added with) this module are:
- isSymmetricPD
- isSymmetricPSD
- is.Xlist
- default.target.fused
- createS
- getKEGGPathway
- kegg.target
- pooledS
- pooledP
- KLdiv.fused
- ridgeP.fused
- optPenalty.fused.grid
- print.optPenaltyFusedGrid
- plot.optPenaltyFusedGrid
- optPenalty.fused.auto
- optPenalty.fused
- default.penalty
- fused.test
- print.ptest
- summary.ptest
- hist.ptest
- plot.ptest
- sparsify.fused
- GGMnetworkStats.fused
- GGMpathStats.fused
 
- The following functions were added to the core module:
- Added miscellaneous (hidden) functions.
Bug fixes:
- Fixed bugs in GGMpathstats:
- Code no longer breaks down if variable names are absent.
- Now properly handles singleton pathsets.
 
- Fixed bug in sparsify: Now always returns symmetric
objects
Adjustments:
- Argument verticleas used in various functions has been
renamed tovertical. Sorry for any inconvenience.
- Internal usage of ridgeSreplaced by the faster
C++-dependent counterpartridgeP
- New features updated conditionNumberPlotfunction:
- Function has been sped up
- Now uses log-equidistant grid for visualization
- Now includes option to additionally plot the approximate loss in
digits of accuracy
 
Notifications:
- ridgeSis deprecated. Please use- ridgePinstead
- Future versions of rags2ridges will be subject to changes in naming
conventions
Version 1.4
Additions:
- Inclusion hidden function .pathContributionfor usage
inGGMpathStatsfunction
- Inclusion hidden function .path2stringfor usage inGGMpathStatsfunction
- Inclusion hidden function .pathAndStatsfor usage inGGMpathStatsfunction
- Inclusion hidden function .cvlfor usage inoptPenalty.LOOCVautofunction
- Inclusion hidden function .lambdaNullDistfor usage inGGMblockNullPenaltyfunction
- Inclusion hidden function .blockTestStatfor usage inGGMblockTestfunction
- Inclusion function that expresses the covariance between a pair of
variables as a sum of path weights: GGMpathStats
- Inclusion function that determines the optimal penalty parameter
value by application of the Brent algorithm to the LOOCV log-likelihood:
optPenalty.LOOCVauto
- Inclusion function that generates the distribution of the penalty
parameter under the null hypothesis of block independence:
GGMblockNullPenalty
- Inclusion function that performs a permutation test for block
structure in the precision matrix: GGMblockTest
- Inclusion wrapper function: fullMontyS
Bug fixes:
- Corrected small error in evaluateSfitfunction. Thedirargument was not properly used previously.
Adjustments:
- New features updated optPenalty.aLOOCVfunction:
- For scalar matrix targets the complete solution path depends on only
1 eigendecomposition and 1 matrix inversion. Meaning: the function is
sped up somewhat by lifting redundant inversions out of forloops.
- Optional graph now plots the approximated LOOCV negative
log-likelihood instead of ln(approximated LOOCV negative
log-likelihood).
- Legend in optional graph has been adapated accordingly.
 
- New features updated optPenalty.LOOCVfunction:
- Optional graph now plots the LOOCV negative log-likelihood instead
of ln(LOOCV negative log-likelihood).
- Legend in optional graph has been adapated accordingly.
 
- New features updated default.targetfunction:
- Inclusion new default target option: type = DIAES.
Gives diagonal matrix with inverse of average of eigenvalues of S as
entries.
 
- New features updated GGMnetworkStatsfunction:
- Now also assesses (and returns a logical) if graph/network is
chordal.
- Now also includes assesment of the eigenvalue centrality.
- Now includes option to have list or table output.
 
- New features updated ridgePathSfunction:
- Sped up considerably for rotation equivariant alternative estimator.
By avoidance of redundant eigendecompositions and inversions.
- Now catches breakdown due to rounding preculiarities when
plotType = "pcor".
 
- New features updated sparsifyfunction:
- Inclusion new thresholding function top: retainment of
top elements based on absolute partial correlation.
- Inclusion output option: When output = "light", only
the (matrix) positions of the zero and non-zero elements are
returned.
- Function no longer dependent on GeneNet; now makes direct use of fdrtool.
- Function now also prints some general information on the number of
edges retained.
 
Version 1.3
Additions:
- Inclusion hidden function .ridgeSifor usage inconditionNumberPlotfunction.
- Inclusion hidden function .eigShrinkfor usage in
(a.o.)ridgeSfunction.
- Inclusion function calculating various network statistics from a
sparse matrix: GGMnetworkStats
- Inclusion function for visual inspection fit of regularized
precision matrix to sample covariance matrix:
evaluateSfit
- Inclusion function for visualization of regularization paths:
ridgePathS
- Inclusion function for default target matrix generation:
default.target
Adjustments and name changes:
- New features updated evaluateSfunction:
- The printed output of the evaluateSfunction is now
aligned
- Calculation spectral condition number has been improved
 
- conditionNumberfunction now called- conditionNumberPlot. The updated function has new features:- 
- Main plot can now be obtained with either the spectral (l2) or the
(approximation to) l1 condition number
- Main plot can now be amended with plot of the relative distance to
the set of singular matrices
- The title of the main plot can now be suppressed
- One can now obtain numeric output from the function: lambdas and
condition numbers
 
- New features updated sparsifyfunction:
- Changed type = c("threshold", "localFDR")tothreshold = c("absValue", "localFDR")(clarifying
nomenclature)
- Changed thresholdtoabsValueCut(clarifying nomenclature)
- Will now output both sparsified partial correlation/standardized
precision matrix and the sparsified precison matrix, when input consists
of the unstandardized precision matrix
 
- New features updated ridgeSfunction:
- Contains an improved evaluation of the target matrix possibly being
a null matrix
- Now evaluates if a rotation equivariant alternative estimator ensues
for a given target matrix
- When rotation equivariant alternative estimator ensues, computation
is sped up considerably by circumventing the matrix square root
 
- optPenaltyCVfunction now called- optPenalty.LOOCV, for sake of (naming) consistency. The
updated function has new features:- 
- targetScaleoption has been removed
- Replaced login optional graph byln
- Visual layout of optional graph now more in line with
recommendations by Tufte (regarding data-ink ratio)
 
- New features updated optPenalty.aLOOCVfunction:
- Replaced login optional graph byln
- Visual layout of optional graph now more in line with
recommendations by Tufte (regarding data-ink ratio)
 
- Computation optimal penalty in conditionNumberPlot,optPenalty.aLOOCVandoptPenalty.LOOCVfunctions sped up considerably for rotation equivariant alternative
estimator. By usage new ridgeS and avoidance of redundant
eigendecompositions
- Default target in ridgeS,conditionNumberPlot,optPenalty.aLOOCVandoptPenalty.LOOCVnow \code{“DAIE” option fromdefault.target
Version 1.2
Additions:
- Inclusion function for ML estimation of the sample covariance
matrix: covML
- Inclusion function for approximate leave-one-out cross-validation:
optPenalty.aLOOCV
- Inclusion function conditionNumberto visualize the
spectral condition number over the regularization path
- Inclusion function evaluateSto evaluate basic
properties of a covariance matrix
- Inclusion function KLdivthat calculates the
Kullback-Leibler divergence between two normal distributions
- Inclusion option to suppress on-screen output in
sparsifyfunction
Bug fixes:
- Corrected small error in optPenaltyCVfunction
Adjustments:
- Both optPenaltyCVandoptPenalty.aLOOCVnow utilizecovMLinstead ofcov
- Default output option in optPenaltyCV(as inoptPenalty.aLOOCV) is nowlight