Removed support for graphical models via package QUIC as QUIC is no longer maintained and was archived on CRAN.
Fixed CRAN checks regarding
all.equal by adding
check.environment = FALSE.
Added reference to stability selection with gamboostLSS.
Make vignettes conditional on suggested packages (closes #24).
Move packages from
Make manuals work without package TH.data.
Speed up examples by adding
\donttest in two occassions.
\doi for DOIs in manual.
Added DOIs to ‘DESCRIPTION’ to fulfill CRAN policies.
Updated ‘README.md’ and vignettes.
Parallel computing via
mc.preschedule = FALSE per default (closes
Make sure that per default
glmnet.lasso selects at maximum
q variables. The previous anti-conservative version
stays available via
args.fitfun = list(type = "anticonservative") (closes
Updated references: Hofner et al (2015) now available at BMC
citation("stabs") for details.
Updated ‘DESCRIPTION’ to be more informative.
fitfuns more quiet (closes
Code contributed by Gokcen Eraslan)
effect in warnings and
error messages (closes
Added example on using
Boosting specific changes: warn if
mstop is to small.
Disallow specification of penalty parameters via
Fixed checks for results of
(closes #17; Code contributed
by Andrey Tovchigrechko)
Fixed citation. (closes #9).
Fix plot labels if matrices are used (as opposed to
Fix issue when variables are dropped from active set in
lars.lasso (closes #5).
Adhere to CRAN policies regarding import of base packages (closes #3).
Changes in ‘inst/CITATION’ to make CRAN happy: Citations can now be extracted without the need to install the package.
Added a function
stabsel.stabsel() to compute (new)
parameter combinations for a fitted
selected() method (originally from
selected() can now be used on stability
selection results to extract selected effects
Added functionality to extract parameters from fitted
run_stabsel to make the actual “fit”
function accessible for other packages.
Added output that states the significance level.
Added new lasso based fit (
function where the
q strongest predictors (according to the
coefficient size) are selected (feature request from Rajen Shah
<R.Shah _at_ statslab.cam.ac.uk>)
Package development moved from R-forge to https://github.com/hofnerb/stabs
stabsel_parameter objects (needed for better outputs)
Added reference to stability selection paper
Made tests conditional on availability of packages
Initial submission to CRAN
stabs implements stability selection for a range of
models, including a novel
matrix interface for
that can be used with generic fit functions.
The code is based on the
stabsel function that was
implemented in mboost until version 2.3-0.
now a generic function with a specialized method for boosting models
that is implemented in mboost. The back-end is now completely
implemented in package stabs.