New: Can now calculate marginal FDR for group lasso/SCAD/MCP with
mfdr()
grpreg 3.5.0
Changed: grpreg()$loss is no longer returned
New: plot_spline() now has “add” option so that splines can be added
to existing plot
Fixed: Loss/deviance now used consistently throughout; see #52
Fixed: Fixed some broken URLs
Fixed: Fixed bug in which mean was added twice for cv.grpreg()
Fixed: Bug in which SNR could be infinite
Fixed: Passing seed no longer affects global environment
Fixed: cv.grpsurv() now sets default group if not supplied
Fixed: No more error if response is constant; see #46
Fixed: No more error if single lambda supplied
Internal: Updated citation format to bibentry()
Internal: Now using R_Calloc for R_USE_STRICT_R_HEADERS
compatibility
Documentation: Now using roxygen
Documentation: Updated online documentation on penalties
grpreg 3.4.0
New: Suite of tools for additive modeling, most notably
expand_spline() and plot_spline() (thank you to Ryan Kurth for her work
on this project)
New: grpreg() now returns linear.predictors object
New: grpreg() and grpsurv() now have residuals() methods
New: predict.grpsurv() can now predict cumulative hazard
(type=“hazard”)
New: Can now perform cross-validation with group bridge in
cv.grpreg()
Changed: fit$y now returns original y, not centered y
Changed: grpsurv() now consistent with grpreg() in terms of
returning deviance (2*loss) and groups as factors
Fixed: predict() no longer converts factors to strings if
type=“groups”
Fixed: grpsurv() works correctly if a single feature is
supplied
grpreg 3.3.1
Fixed: AUC() now compatible with survival 3.2.10
Fixed: predict() now works correctly for cv.grpsurv objects
Internal: Fixed memory leak
Documentation: Better formatting of references, with DOIs
grpreg 3.3.0
Fixed: sqrt(K) no longer hard-coded into discarding rules (thank you
to Dan Kessler for pointing this out)
Testing: Now uses the tinytest package
Documentation: Removing references to grpregOverlap (hope to
merge)
grpreg 3.2.2
Change: Better error detection for ill-conditioned, unpenalized
matrices
Fixed: loss.grpsurv now works for total=FALSE
Internal: Lots of internal changes for cleaner, more reliable
code
New version numbering system
grpreg 3.2-1
Change: Cross-validation now balances censoring across folds for
survival models
Fixed: Leave-one-out cross-validation now works correctly for
logistic regression
grpreg 3.2-0
New: cv.grpsurv now calculates SE, with bootstrap option
Change: R^2 now consistently uses the Cox-Snell definition for all
types of models
Change: Survival loss now uses deviance
Change: cv.grpsurv now uses ‘fold’, not ‘cv.ind’, to declare
assignments
Fixed: cv.grpreg now correctly handles out-of-order groups for
Poisson
Fixed: cv.grpsurv now correctly standardizes out-of-order
groups
Fixed: grpreg no longer returns loss=NA with family=‘binomial’ for
some lambda values
Internal: SSR-BEDPP optimization reinstated after bug fix
Internal: C code for binom/pois combined into gdfit_glm,
lcdfit_glm
Documentation: Lots of updates
Documentation: vignette now html (used to be pdf)
Documentation: pkgdown website
grpreg 3.1-4
Fixed: Works with arbitrarily “messy” group structures now (constant
columns, out of order groups, etc.) due to restructuring of
standardization/ orthogonalization
Internal: SSR-BEDPP rule turned off due to bug
grpreg 3.1-3
Internal: C code now uses || instead of |
grpreg 3.1-2
Fixed: Bug in applying screening rules with group lasso for linear
regression with user-specified lambda sequence (thank you very much to
Natasha Sahr for pointing this out)
grpreg 3.1-1
Fixed: Cross-validation no longer fails when constant columns are
present (thank you to Matthew Rosenberg for pointing this out)
Fixed: Cross-validation no longer fails when group.multiplier is
specified
grpreg 3.1-0
New: Additional tests and support for coersion of various types with
respect to both X and y
Change: Convergence criterion now based on RMSD of linear
predictors
Change: ‘Lung’ and ‘Birthwt’ data sets now use factor representation
of group, as character vectors are inherently ambiguous with respect to
order
Change: max.iter now based on total number of iterations for entire
path
Internal: ‘X’, ‘group’, and ‘group.multiplier’ now bundled together
in an object called ‘XG’ to enforce agreement at all times
Internal: new SSR-BEDPP feature screening rule for group lasso
Internal: Registration of native routines
Internal: Changing PROTECT/UNPROTECT to conform to new coding
standards
Fixed: The binding of X and G fixes several potential bugs,
including Issue #12 (GitHub)
grpreg 3.0-2
Fixed bug involving mismatch between group.multiplier and group if
group is given out of order.
grpreg 3.0-1
Fixed: memory allocation bug
Deprecation: Re-introduced ‘birthwt.grpreg’ for backwards
compatibility, but this is deprecated
New: option to return fitted values from cross-validation folds
(returnY=TRUE) to cv.grpreg and cv.grpsurv
New: Added user interrupt checking
Change: Reformatted (and renamed) example data set ‘Birthwt’; added
example data set ‘Lung’ for survival
Internal: Greatly expanded suite of tests; various bugs identified
and fixed as a result
Documentation: Added vignettes (a quick-start guide and a detailed
description of available penalties)
grpreg 2.8-1
New: cv.grpreg now allows user to specify lambda (thanks to Vincent
Arel-Bundock for suggesting this change)
Fixed: bug for predict.grpreg(fit, type=“nvars”) or type=“ngroups”
when scalar lambda value is passed
Documentation: Updated citations
grpreg 2.8-0
New: More flexible interface through the ‘group’ argument; groups
may now be out of order, and may be named rather than only consecutive
integers
New: ‘X’ can now be a matrix of integers (previously this would
result in the passing of an incompatible storage type to C)
New: Additional error checks to prevent cryptic error messages
Internal: modifications to convergence monitoring
New: Added corrected AIC and extended BIC as options with
select()
Change: summary.cv.grpreg now describes multitask learning models
more accurately
Fixed: bug for multitask learning when number of outcomes = 2 (thank
you to Aluma Dembo for pointing this out)
Fixed: Cross-validation for multitask learning now respects the
multivariate structure of the response matrix
Fixed: bug in cv.grpreg when attempting to use leave-one-out
cross-validation
grpreg 2.7-1
Fixed: More rigorous initialization at C level to prevent possible
memory access problems
Fixed: predict() for types ‘vars’, ‘nvars’, and ‘ngroups’ with
multivariate outcomes
Fixed: As a consequence of the above fix, summary(cvfit) now works
for multivariate outcomes (thank you to Cajo ter Braak for pointing out
that this was broken)
grpreg 2.7-0
New: support for Poisson regression
Internal: .Call now used instead of .C
Fixed: bug in cv.grpreg when attempting to use leave-one-out
cross-validation (thank you to Cajo ter Braak for pointing this
out)
grpreg 2.6-0
Internal: Various internal changes to make the package more
efficient for large data sets
grpreg 2.5-0
New: group exponential lasso ‘gel’ method
New: ‘gmax’ option
New: ‘nvars’ and ‘ngroups’ options for predict
Change: appearance of summary.cv.grpreg display
grpreg 2.4-0
New: options in plot.cv.grpreg to plot estimates of r-squared,
signal-to-noise ratio, scale parameter, and prediction error in addition
to cross-validation error (deviance)
New: grpreg and cv.grpreg now allow matrix y to facilitation group
penalized methods for seemingly unrelated regressions/multitask
learning. This is something of a ‘beta’ release at this point, and will
be developed and refined further in future releases.
New: ‘summary’ method for cv.grpreg objects
New: ‘coef’ and ‘predict’ methods for cv.grpreg objects
Change: Brought gBridge up to date so that it now handles constant
columns, etc. (see # grpreg 2.2-0)
Fixed: bug in predict type=‘coefficients’ when ‘lambda’ argument
specified
Fixed: bug in cv.grpreg with user-defined lambda values
grpreg 2.3-0
Internal: Switched to SVD-based orthogonalization to allow for
linear dependency within groups
grpreg 2.2-1
Fixed: compilation error for 32-bit Windows
Fixed: bug in calculation of binomial deviance when fitted
probabilities are close to 0 or 1
grpreg 2.2-0
New: select now Now allows ‘…’ options to be passed to logLik
New: Added option to plot norm of each group, rather than individual
coefficients
New: ‘vars’, ‘groups’, and ‘norm’ options added to ‘predict’
Change: cv.grpreg now returns full data fit as well as CV errors;
this allows cv.grpreg to handle constant columns and fixes some
bugs
Fixed: logLik no longer calculates (meaningless) log-likelihoods for
saturated models (thank you to Xiaowei Ren for pointing this out)
Fixed: bug for returning group when some groups were eliminated due
to constant columns
grpreg 2.1-0
New: grpreg can now handle constant columns (they produce
beta=0)
Fixed: Bug involving orthogonalization with unpenalized groups
Internal: restructuring of C code
grpreg 2.0-0
New: Group MCP, group SCAD methods added
New: Added ‘cv.grpreg’ to facilitate cross-validation
New: ‘dfmax’ option
New: ‘group.multiplier’ option
New: Allows specification of unpenalized groups
Change: gBridge now divorced from grpreg and given separate
function
Internal: New algorithm for group lasso
Internal: Extensive internal refactoring of code
Internal: standardize and orthogonalize functions added
Internal: Much more extensive and reproducible code testing
grpreg 1.2-0
New: grpreg now returns ‘loss’
New: Added logLik method
Change: Syntax of ‘select’ modified (no longer requires X, y to be
passed)
Change: ‘plot.grpreg’ function more flexible
Change: ‘n.lambda’ to ‘nlambda’ in grpreg
Change: ‘a’ to ‘gamma’ for MCP tuning parameter
Change: ‘lambda2’ to ‘alpha’
Removed: ‘monitor’ no longer an option in grpreg
Removed: ‘criteria’ option for select
Fixed: Bug in calculation of df for gLasso (grpreg.c)
Documentation: Updated citation and contact information