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:
Fixed URLs.
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 ridgeP output.
Version 2.2.3
Documentation:
Updated CITATION file
Updated README file
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.
GGMpathStats now 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.
CNplot function 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.LOOCV is deprecated. Please use
optPenalty.kCV instead
optPenalty.LOOCVauto is deprecated. Please use
optPenalty.kCVauto instead
Version 2.1.1
Documentation:
Updated CITATION file
Updated README file
Adjustments:
sparsify now has an additional thresholding option:
‘connected’
Version 2.1
Documentation:
Updated CITATION file
Updated README file
Bug fixes:
Fixed bug in Ugraph:
Incorrectly stated before that all igraph layouts were
supported.
Now they indeed are supported.
Notifications:
conditionNumberPlot is deprecated. Please use
CNplot instead
Features of the CNplot function (above and beyond
conditionNumberPlot):
The digitLoss and rlDist arguments have
been removed
These arguments have been replaced with the logical argument
Iaids
Iaids = TRUE amends 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 main is now a character argument
Argument value now by default takes the value 1e-100
(convenient)
Now uses C++ functionalty for additional speed
Adjustments:
edgeHeat now has aligned x-axis labels
The visualizations of the optPenalty.LOOCV and
optPenalty.aLOOCV functions now will no longer produce
horizontal and/or vertical lines that fall outside the boundaries of the
figure
optPenalty.LOOCV now uses log-equidistant penalty grid
for optimal penalty parameter determination (this also enhances the
visualization)
New features updated optPenalty.aLOOCV function:
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 Ugraph function:
One can now also specify vertex placement by coordinate
specification
Now outputs, for convenience, the vertex coordinates of the plotted
graph
ridgePathS has been sped up by killing redundant
inversion
The covML function 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.LOOCVauto function has been amended with
an argument that indicates if the evaluation of the LOOCV score should
be performed on the correlation scale
The optPenalty.LOOCV function has been amended with an
argument that indicates if the evaluation of the LOOCV score should be
performed on the correlation scale
The optPenalty.aLOOCV function 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 NEWS file!
Updated (and corrected) CITATION file
Added README file
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:
covMLknown
GGMmutualInfo
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 verticle as used in various functions has been
renamed to vertical. Sorry for any inconvenience.
Internal usage of ridgeS replaced by the faster
C++-dependent counterpart ridgeP
New features updated conditionNumberPlot function:
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:
ridgeS is deprecated. Please use ridgeP
instead
Future versions of rags2ridges will be subject to changes in naming
conventions
Version 1.4
Additions:
Inclusion hidden function .pathContribution for usage
in GGMpathStats function
Inclusion hidden function .path2string for usage in
GGMpathStats function
Inclusion hidden function .pathAndStats for usage in
GGMpathStats function
Inclusion hidden function .cvl for usage in
optPenalty.LOOCVauto function
Inclusion hidden function .lambdaNullDist for usage in
GGMblockNullPenalty function
Inclusion hidden function .blockTestStat for usage in
GGMblockTest function
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 evaluateSfit function. The
dir argument was not properly used previously.
Adjustments:
New features updated optPenalty.aLOOCV function:
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 for
loops.
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.LOOCV function:
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.target function:
Inclusion new default target option: type = DIAES.
Gives diagonal matrix with inverse of average of eigenvalues of S as
entries.
New features updated GGMnetworkStats function:
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 ridgePathS function:
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 sparsify function:
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 .ridgeSi for usage in
conditionNumberPlot function.
Inclusion hidden function .eigShrink for usage in
(a.o.) ridgeS function.
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 evaluateS function:
The printed output of the evaluateS function is now
aligned
Calculation spectral condition number has been improved
conditionNumber function 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 sparsify function:
Changed type = c("threshold", "localFDR") to
threshold = c("absValue", "localFDR") (clarifying
nomenclature)
Changed threshold to absValueCut
(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 ridgeS function:
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
optPenaltyCV function now called
optPenalty.LOOCV, for sake of (naming) consistency. The
updated function has new features:
targetScale option has been removed
Replaced log in optional graph by ln
Visual layout of optional graph now more in line with
recommendations by Tufte (regarding data-ink ratio)
New features updated optPenalty.aLOOCV function:
Replaced log in optional graph by ln
Visual layout of optional graph now more in line with
recommendations by Tufte (regarding data-ink ratio)
Computation optimal penalty in conditionNumberPlot,
optPenalty.aLOOCV and optPenalty.LOOCV
functions sped up considerably for rotation equivariant alternative
estimator. By usage new ridgeS and avoidance of redundant
eigendecompositions
Default target in ridgeS,
conditionNumberPlot, optPenalty.aLOOCV and
optPenalty.LOOCV now \code{“DAIE” option from
default.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 conditionNumber to visualize the
spectral condition number over the regularization path
Inclusion function evaluateS to evaluate basic
properties of a covariance matrix
Inclusion function KLdiv that calculates the
Kullback-Leibler divergence between two normal distributions
Inclusion option to suppress on-screen output in
sparsify function
Bug fixes:
Corrected small error in optPenaltyCV function
Adjustments:
Both optPenaltyCV and optPenalty.aLOOCV
now utilize covML instead of cov
Default output option in optPenaltyCV (as in
optPenalty.aLOOCV) is now light