NEWS  R Documentation 
News for Package 'mboost'
Changes in mboost version 2.911 (20240819)
Bugfixes
Fix Rd formatting issues
Use
R_Calloc
Changes in mboost version 2.910 (20240429)
Bugfixes
Fix Rd formatting issues
Disable tests requiring kangar00
Changes in mboost version 2.99 (20231207)
Bugfixes
Fix Rd formatting issues
Changes in mboost version 2.98 (20230806)
Bugfixes
S3 argument mismatch
include
R_ext/BLAS.h
Changes in mboost version 2.97 (20220425)
Bugfixes
Don't escape &
Changes in mboost version 2.96 (20220406)
Bugfixes
Fix BLAS problem.
More ‘\dontrun’ in manual packages
Changes in mboost version 2.95 (20210406)
Bugfixes

btree(..., by = )
caused problems when restricting the number of boosting iterations.
Miscellaneous
Speedup vignettes.
Use less precision in numerical vignette outputs.
Changes in mboost version 2.94 (20201209)
Uservisible changes
New maintainer: Torsten Hothorn follows Benjamin Hofner, who curated the 2.62.9 series, as maintainer. All authors thank Benny for 4 years of package maintainance!
Added
by
argument tobtree
; only binary factors are allowed.
Bugfixes
Add missing
rclass
function to derive class predictions from conditional class probabilities toBinomial()
family.Plot correct xaxis in
plot(cvrisk(...))
(closes #102).
Changes in mboost version 2.93 (20200806)
Bugfixes
Removed deprecated argument
LINPACK
from all calls tosolve
. Fixes #109.
Changes in mboost version 2.92 (20200217)
Bugfixes
Fixed minor bug in
plot.cvrisk
. Fixes #96.Really check for leaveoneout crossvalidation if
CoxPH
was used.Fixed minor bug in documentation:
...
was described in documentation but was not used in function. Fixes #105.Fixed a minor issue with special contrast
"contr.dummy"
.
Miscellaneous
Fixed typo in vignette.
Changes in mboost version 2.91 (20180821)
Bugfixes
Dropped
\itemize
in ‘ins/NEWS.Rd’. Fixes #94.
Changes in mboost version 2.90 (20180608)
Uservisible changes
Added family
RCG
for ratio of correlated gammas and downstream test, see Weinhold et al. (2016). Closes #86.Removed corrected crossvalidation for Cox models (Verweij and van Houwelingen, 1993) as it was not working. Closes #85.
Use
partykit::ctree
instead ofparty::ctree
inbtree
andblackboost
. This is slower but more flexible.Allow multivariate negative gradients. Note that all elements are updated simultaneously, which in most cases is NOT what you want (but in rare cases it is the right thing to do).
Allow the specification of either
mstop
orgrid
instabsel
.Allow leaveoneout crossvalidation (via
type = "kfold"
).
Bugfixes
Throw error when data is not compatibel (instead of silently recycling the vector). Fixes #79.
Fixed handling of
offset
for familiesNBinomial
andHurdle
. Closes #88.Replace
cBind
(now deprecated) withcbind
. Fixes #90.Fix
predict
with zero iterations (names were not correctly assigned). Fixes #87.Fixed labels in plot function for categorical baselearners.
Miscellaneous
Added further tests / checks.
Removed unused functions (
response
) and arguments (bnames
fromextract.glmboost
).Update email address and added ORCIDs.
Changes in mboost version 2.81 (20170719)
Uservisible changes
Added all possible options to the specific boosting functions instead of passing the options via
...
tomboost_fit
. Closes #81.
Miscellaneous
Minor speed ups in
df2lambda
(i.e., when computing penalty parameter for the defined degrees of freedom). Changes proposed by Benjamin Christoffersen.Updated kernel boosting reference. Closes #84.
Rebuilt package with LF instead of CRLF to fix ‘cleanup’ script as requested by CRAN. Fixes #82
Use "old" definition of degrees of freedom in
vignette("mboost", package = "mboost")
to make results reproducible.
Bugfixes
Fix handling of missing values in
mboost
andgamboost
when weights are specified. Fixes #80.
Changes in mboost version 2.80 (20170504)
Uservisible changes
Models with zero steps (i.e., models containing only the offset) can now be fitted. Furthermore, crossvalidation can now also select a model without baselearners. Fixes #64, #66, and #69.

Binomial
now uses link functions by making use ofmake.link
. Furthermore, an alternative implementation ofBinomial
models along the lines of theglm
implementation can be used viaBinomial(type = "glm")
. Additionally, it works not only with a twolevel factor but also with a twocolumn matrix containing the number of successes and number of failures. Fixes #34, #63 and #65. Added new baselearner
bkernel
for kernel boosting as described inS. Friedrichs, J. Manitz, P. Burger, C.I. Amos, A. Risch, J.C. ChangClaude, H.E. Wichmann, T. Kneib, H. Bickeboeller, and B. Hofner (2017), PathwayBased Kernel Boosting for the Analysis of GenomeWide Association Studies. Computational and Mathematical Methods in Medicine. 2017(6742763), 117. doi:10.1155/2017/6742763.
Removed check if
df2lambda
is stable. Hence,options(mboost_check_df2lambda)
(introduced in mboost 2.50) is no longer used. Closes #26.
Miscellaneous
Added Andreas Mayr as contributor.
Updated references and added reference to
citation("mboost")
.Fixed code of India example, which can be used to reproduce the data analysis presented in
N. Fenske, T. Kneib, and T. Hothorn (2011), Identifying risk factors for severe childhood malnutrition by boosting additive quantile regression. Journal of the American Statistical Association, 106:494510.
(see
system.file("India_quantiles.R", package = "mboost")
)Fixed package citation.
Register C routines to make CRAN happy (again). Fixes #77.
Bugfixes
Make sure that
family = Multinomial
is only used with Kronecker product baselearners. Fixes #46.Use argument
PACKAGE
in.Call
. Fixes #72.If
center
is specified as boolean value inbols
, we now throw an error. Fixes #70.Fixed
AUC
family which expected fit to be equal to a constant in the first iteration.Check for new data, e.g., in
predict
, was broken. Fixes #68.Make sure that
newdata
is discarded infitted
. Fixes #76.
Changes in mboost version 2.70 (20161123)
Uservisible changes
New
Cindex
family to optimize survival models w.r.t. the concordance index. Fixes #53.Added function
varimp
to extract variable importance. A dedicated plot function exists (plot(varimp())
). Code was provided by Tobias Kuehn and Almond Stoecker. See pull request #29.Improved
plot
function for boosting models:
plot
fails earlier in case of multiplelevelplots
, i.e., maps (thanks to Mikko Korpela). See pull request #39. Provide sensible defaults for
xlab
andylab
and allow userspecified axis labels for bi and multivariate plots. Fixes #51.Export
plot
functions (plot.glmboost
,plot.mboost
,lines.mboost
,plot.varimp
andplot.cvrisk
) for better usability and visibility.

Miscellaneous
Updated manual regarding the usage of families and clarified the usage of argument
qoffset
.Updated manual for baselearners:
Highlight that
x
should be centered ifbols(x, intercept = FALSE)
is used.Discourage using
bbs(, constraint != "none")
; Preferably usebmono
for constrained effect estimates. Fixes #36.
Improved vignettes (thanks to Mikko Korpela). See pull request #38.
Bugfixes
Solve potential problem with
IPCweights()
. Fixes #54.Drop unobserved factor levels from
bols()
. Fixes #47.Adapt
btree
to changes introduced in package party. Fixes #58.Improved
cvrisk
to be more robust in various use cases (thanks to Mikko Korpela). See pull request #42.Be more careful regarding namespace scoping rules. Fixes #45.
Changes in mboost version 2.60 (20160311)
Uservisible changes
New maintainer: Benjamin Hofner follows Torsten Hothorn as maintainer.
Package party is now imported. mboost no longer directly relies on unexported functions.
Allow extrapolation for predictions if kronecker products, tensor products or sums are used. Fixes #23.
Development now hosted entirely on github as boostR/mboost.
Started using testthat.
Miscellaneous
Improved checks for
newdata
: Warnings are no longer issued if data has just different types of numeric values (i.e., integer vs. double). Resolves issue #17.Fixed ‘CITATION’ by removing duplicated string 'R package version' (spotted by Heidi Seibold).

predict
: Improve warning whenlength(offset) > 1
. Closes issue #20. Added test coverage using package covr.
Better error handling in
cvrisk
also for parallel processes.Suppress warning of
rankMatrix
. (Resolves issue #24).Stop exporting internal functions for FDboost. Use
mboost_intern()
instead. Caution: Do not use this function.
Bugfixes
Handling of missing values has been improved. Resolves issue #12.
Minor bug fixed in vignette ‘mboost_illustrations.Rnw’.
Throw an error if model cannot be fitted. Fixes issue #18.
Fixed bug in bkronecker with dense matrices. Resolves issue #30.
Changes in mboost version 2.50 (20150813)
Uservisible changes
Added documentation for
plot.mboost
function and moved documentation ofplot.glmboost
to the same help page. Resolves issue #14.
bbs
andbmono
no longer allow data outside of theboundary.knots
during model fitting. Predictions for
bbs
andbmono
now use linear extrapolation (user request inspired bymgcv::Predict.matrix.pspline.smooth
).Better handling of errors in (single) folds of
cvrisk
: results of folds without errors are used and awarning
is issued.Parallel computing via
mclapply
: Setmc.preschedule = FALSE
per default.Added new option
options(mboost_check_df2lambda = TRUE)
, which controls if a stability check indf2lambda
is performed. If set toFALSE
this might speed up the computation ofdf2lambda
especially with large design matrices.Prediction now also possible with
newdata = list()
. Resolves issue #15.
Miscellaneous

PropOdds()
: Updated manual for proportional odds model. 
Multinomial()
: Updated manual for multinomial logit model. Predictions for new data are now possible (resolves issue #13, thanks to Sarah Brockhaus). 
‘inst/CITATION’: Added subheadings and tutorial paper.
Stopped computing the singular vectors in
df2lambda
as the singular values are sufficient and as “computing the singular vectors is the slow part for large matrices” (proposed by Fabian Scheipl).
Bugfixes
Fixed bug in
PropOdds()
which occurred ifoffset
was specified: nuisance parametersdelta
andsigma
were not properly initialized (spotted by Madlene Nussbaum).Bug in
plot.mboost()
fixed which occurred if a factor with equal effect estimates for different categories was plotted.Bug in
df2lambda
fixed: Make sure thatA
is symmetric if it isMatrix
object (spotted by Souhaib Ben Taieb).Bug in
df2lambda
fixed. Design matrices were always assumed to be of full rank.Truncate output of complete data structure when model is printed. Resolves issue #11.
Adhere to CRAN policies regarding import of base packages (closes #9).
Changes in mboost version 2.42 (20150212)
Uservisible changes
Export
df2lambda
,hyper_bbs
andbl_lin
to make package FDboost happy. Note: These functions usually should not be called directly by users.
Miscellaneous
Added Hothorn et al (2010) to ‘inst/CITATION’
Bugfixes
Changes in ‘inst/CITATION’ to make CRAN happy: Citations can now be extracted without the need to install the package.
Removed
EISPACK = FALSE
fromeigen()
as the argument is defunct and ignored.Changed
require
torequireNamespace
Changes in mboost version 2.41 (20141215)
Miscellaneous
Moved generic definition of
selected
to stabs which is required anyway (thus, stabs >= 0.50 is now required)load AML dataset (‘AML_Bullinger.rda’) from package TH.data
Updated references (for stability selection, confidence intervals and constrained regression)
fixed ‘inst/CITATION’
Refer to
news(package = "mboost")
instead of to the ‘NEWS’ file.
Bugfixes
Crossvalidation was potentially wrong for
CoxPH()
models. Users can now choose if they want the naive crossvalidation or the improved version by Verweij and van Houwelingen (1993); (spotted by Holger Reulen <hreulen _ at _ unigoettingen.de>)Examples in
\dontrun
are now executable and all dependencies are properly stated in ‘DESCRIPTION’
Changes in mboost version 2.40 (20141002)
Uservisible changes
Added
confint
function to compute (bootstrap) confidence intervals together with plot and print methods
stabsel()
now depends on the new package stabs where the back end and methods such asplot
andprint
are implemented Improved
plot
method for varying coefficients (ylim
now suitable) and baselearners of factor variables.Tweaked
update
function: we now can turn thetrace
on and off, and specify the type ofrisk
as well as theoobweight
toupdate()
Miscellaneous
Updated vignette ‘mboost_tutorial’ to reflect latest changes in mboost.
Changed plain text ‘NEWS’ to ‘inst/NEWS.Rd’
Removed links to archived package mfp.
Explicitly specify the packages for functions that are implemented in packages that are listed as
Suggests:
, e.g we now useparty::ctree_control
etc.
Bugfixes

glmboost()$model.frame()
was broken 
glmboost()$update()
was broken 
predict()
for models with nonscalar offsets was broken
Changes in mboost version 2.30 (20140626)
Uservisible changes

stabsel
was recoded and now uses different terminology, much more options and a better tested code base new replacement function
mstop<
as an alternative to<mboost>[i]
(suggested by Achim Zeileis).
bmono
new and faster algorithm to compute monotonic Psplines (
type = "quad.prog"
)new constraints added for positive and negative spline estimates

bbs
allows monotone Tsplines (experimental)
new argument
deriv
to bbs for computing derivatives of Bsplines

bmrf
can now also handle neighborhood matrices as an argument tobnd
added new families
Hurdle
andMultinomial

boost_control
: added new argumentstopintern
for internal stopping (based on oobag data) during fitting All data sets have been moved to the new package set TH.data
Miscellaneous
added new argument
which
tovariable.names()
added new method
risk
to extract risks
brandom
now checks that a factor is given speed improvements when updating a model via
mod[mstop]
changed
\dontrun
to\donttest
updated references
Bugfixes
fixed a problem with
extract()
of single baselearnersfixed bug in
AIC.mboost
:df = "actset"
can only be used with glmboost modelsfixed package start up messages
fixed a problem in
mboost_fit
(when names of baselearners were missing)
Changes in mboost version 2.23 (20130909)
fixed bugs in survival families:

offset
in all survival families was based onmax(survtime)
instead ofmax(log(survtime))
; 
offset
inCoxPH
can't be computed from Cox Partial LH as constants are canceled out; Use fixedoffset
instead;

speed up checking of manual by changing some computations (e.g. reduce
mstop
) or exclude code from checking via\dontrun{}
removed dependency on ipred (replaced with TH.data)
small improvements in manual
Changes in mboost version 2.22 (20130208)

bbs(..., center = "spectralDecomp")
computes the spectral decomposition of the penalty matrix and the penalized part of the design matrix is defined by this decomposition.Experiments show that
bols(x) + bbs(x, center = "spectralDecomp")
is a little better in recovering the true underlying functions than the defaultbols(x) + bbs(x, center = TRUE)
or, equivalently,bols(x) + bbs(x, center = "differenceMatrix")
.For
bbs(x, y, center = TRUE)
orbmrf(x, center = TRUE)
, the spectral decomposition is (and was) always used. fixed bug in
stabsel
:'...'
was not passed tocvrisk
and thus one could not specify options formclapply
fixed bug in
brandom
: now really usecontrasts.arg = "contr.dummy"
per default.removed
tests/
folder and.Rout.save
files for vignettes from the CRAN releasesmall improvements in manual
Changes in mboost version 2.21 (20130114)
included warnings in
stabsel()
for better guidance of the user:A warning is issued if the upper bound for the
FWER
in stability selection is greater (by a certain margin) than the specified bound.A warning is also issued if
mstop
is too small to selectq
variables.
improved output of errors and warnings in
stabsel
.suppress the notes from package Matrix about method ambiguity (
"Note: method with signature ... chosen, ... would also be valid"
)updated manual on baselearners to reflect the change in the default for degrees of freedom (additionally, all options are now discussed in a separate section of the baselearner manual)
updated vignette ‘mboost_tutorial’
updated ‘mboost_package.Rd’: now all important changes since mboost 2.0 are documented there
changed roles of contributors to
ctb
suggested packages are now only used inside
if(require(pkg))
statementschanged start up message
Changes in mboost version 2.20 (20121121)
switch from packages multicore and snow to parallel
changed behavior of
bols(x, intercept = FALSE)
whenx
is a factor:now the intercept is simply dropped from the design matrix
coding can be specified as usually for factors.
changed default for
options("mboost_dftraceS")
toFALSE
, i.e., degrees of freedom are now computed from smoothing parameter as described in B. Hofner, T. Hothorn, T. Kneib, M. Schmid (2011).changed computation of Bspline basis at the boundaries: now also use equidistant knots in the boundaries (per default)
improved
plot
function when dealing with spatial plots (now builds suitable grid based on the observations if nonewdata
is given)increased default number of subsampling replicates in
stabsel
to 100[experimental]
bmono()
now implements constraints at the boundaries of (monotonic) Psplines[experimental] added family
Gehan()
for rankbased estimation of survival models in an accelerated failure time framework (contributed by Brent Johnson bajohn3@emory.edu)
Changes in mboost version 2.13 (20120927)
matrices with one column are now handled as vectors in baselearners
improved manual
fixed error that occurs with R (>= 2.16) due to internal changes in R
Changes in mboost version 2.12 (20120229)
improved handling of missing values (throws warnings and fixed a bug that occurred for missings in the response)
improved manual for the handling of contrasts in bols
added tutorial vignette
updated references
Changes in mboost version 2.11 (20111128)
new option "mboost_eps" for factor in DemmlerReinsch orthogonalization
Changes in mboost version 2.10 (20111115)
Baselearners
added baselearners for smooth monotonic (or convex/concave) functions of one or two variables (bmono())
added baselearners for radial basis functions (brad())
added baselearners for Markov random fields (bmrf())
bbs(x, cyclic = TRUE) for cyclic covariates ensures that predictions at the boundaries coincide and that the resulting function estimate is smoothly joined
bols(x, intercept = FALSE) only reasonable if x is centered. A warning is now issued if x is not centered.
changed default for degrees of freedom in bspatial() to df = 6
added checks in bbs (and brandom) to ensure that the specified degrees of freedom are greater than the range of the (unpenalized) null space
bolscw can be mixed with other baselearners (although not yet exported and not via the formula interface)
new experimental baselearner %O% for smoothing matrixvalues responses
Families
add Binomial(link = "probit") and general cdf's as link functions (experimental)
added new families:
AUC() for AUC loss function
GammaReg() for gamma regression models
Methods
added extract() methods for baselearners and fitted models
added residuals() function to extract residuals from the model
improved predict.mboost(): added names where missing and the offset as attribute where applicable.
fixed bug in predict() with glmboost.matrix(..., center = TRUE)
coef now also works with tree baselearners (returns NULL in this case)
changed coef.gamboost to coef.mboost
various improvements in plot.mboost function
Miscellaneous
changed default in glmboost() to center = TRUE
speed up glmboost() a little bit
changed behavior of cvrisk() if weights are used: outofbagrisk now weighted according to "weights" as specified in call to mboost
added warning if df2lambda is likely to become numerically unstable (i.e. in the case of large entries in the design matrix)
improved storage, speed and stability using Matrix technology for bols() for factors with many levels and brandom(); further improvements in baselearners that are combined via %+%.
various improvements and fixes in manuals
Changes in mboost version 2.012 (20110822)
minor bugfixes to make mboost work with gamboostLSS
replaced writeLines with packageStartupMessage in .onAttach()
replaced partially matched function arguments by full arguments
minor fixes in manuals
Changes in mboost version 2.011 (20110317)
fix problem in bl_lin when using dense matrices from package "Matrix"
Changes in mboost version 2.010 (20110220)
add rqss results for India childhood malnutrition data
Changes in mboost version 2.09 (20101119)
add gbm to Suggests
Changes in mboost version 2.08 (20101111)
make survival package happy again
Changes in mboost version 2.07 (20100928)
vignette "mboost" updated
remove problem with R CMD check that occurred on some 64bit systems
Changes in mboost version 2.06 (20100522)
no not use multicore functionality in R CMD check, really.
Changes in mboost version 2.05 (20100521)
no not use multicore functionality in R CMD check
Changes in mboost version 2.04 (20100415)
new vignette "mboost" describing 2.0x series features
fixed bug in bols(): contrast.arg was ignored if not a named list (which is wasn't per default)
added (missing) response functions to families Weibull(), Loglog(), Lognormal() and NBinomial()
fixed bug in family CoxPH which occurred with NAs
improvements and corrections in documentation
Changes in mboost version 2.03 (20100310)
glmboost(..., center = TRUE) now also centers columns of the design matrix corresponding to contrasts of factors when an intercept term is present leading to faster risk minimization in these cases.
coef.glmboost: New argument
off2int = TRUE
adds the offset to the intercept. In addition, the intercept term is now adjusted for centered covariates.check for infinite residuals in mboost_fit(). Especially for family = Poisson(), something like boost_control(nu = 0.01) fixes this problem.
"by" (in bols() and bbs()) can now handle factors with more than two levels
improved plot.mboost() for varying coefficients
minor improvements in documentation
Changes in mboost version 2.02 (20100304)
fixed bug in helper function get_index, which caused (in some circumstances) wrong handling of factors in gamboost() (spotted by Juliane Schaefer <JSchaefer _at_ uhbs.ch>)
reduce memory footprint in blackboost (requires party 0.99993)
Changes in mboost version 2.01 (20100301)
fixed bug in coef( , aggregate = "cumsum"): fraction "nu" was missing
Changes in mboost version 2.00 (20100201)
generic implementation of componentwise functional gradient boosting in
mboost_fit
, specialized code for linear, additive and interaction models removednew families available for ordinal, expectile and censored regression
computations potentially based on package Matrix (reduces memory usage)
various speed improvements
added interface to extract selected baselearners (selected())
added interface for parallel computations in cvrisk with arbitrary packages (e.g. multicore, snow)
added "which" argument in predict and coef functions and improved usability of "which" in plotfunction. Users can specify "which" as numeric value or as a character string
added function cv() to generate matrices for kfold crossvalidation, subsampling and bootstrap
new function stabsel() for stability selection with error control
added function model.weights() to extract the weights
added interface to expand model by increasing mstop in model[mstop]
alternative definition of degrees of freedom available
Interface changes:
class definition / Family() arguments changed
changed behavior of subset method (model[mstop]). Object is directly altered and not duplicated
argument "center" in bols replaced with "intercept"
argument "z" in baselearners replaced with "by"
bns and bss deprecated;
Changes in mboost version 1.14 (20091118)
fixed bug in prediction with varying coefficients for binary effect modifiers
Changes in mboost version 1.13 (20090921)
better xaxes in plot.cvrisk and possibility to change xlab
parallel cvrisk on Unix systems only (multicore isn't safe on windows)
included new penalty for ordinal predictors (in bols())
corrected bug in bspatial (centering was not used for Xna)
removed output of dfbase (which is seldom used) in gamboost
changed manual for coef.gamboost
make sure NAs are handled correctly when center = TRUE in glmboost
Changes in mboost version 1.12 (20090721)
better weights and boundary knots handling in bspatial
cvrisk runs in parallel if package multicore is available
errors removed and minor improvements in the manuals
center = TRUE in glmboost did only apply to numeric (not integer) predictors
for safety reasons: na.action = na.omit again (causes slight changes in wpbc3 example)
Changes in mboost version 1.11 (20090421)
new quantile regression facilities.
fix problem with bbs baselearner and cvrisk
Changes in mboost version 1.10 (20090327)
bbs instead of bss is the default baselearner in gamboost
make sure bbs with weights and expanded observations returns numerically the very same results
btree can now deal with multiple variables
new gMDL criterion (contributed by Zhu Wang <zhu.wang@yale.edu>)
make survival package happy again
Changes in mboost version 1.06 (20090109)
bols allows to specify nondefault contrasts.
Changes in mboost version 1.05 (20081202)
remove experimental memory optimization steps
Changes in mboost version 1.04 (20081112)
negative gradient of GaussClass() was wrong, spotted by Kao Lin <linkao@picb.ac.cn>
Changes in mboost version 1.03 (20081107)
Date was malformed in DESCRIPTION
Changes in mboost version 1.02 (20081105)
improved memory footprint in gamboost() and cvrisk()
option to suppress saving of ensembles added to boost_control()
bbs(), bns(), bspatial(): default number of knots changed to a fixed value (= 20)
changed default for grid (now uses all iterations) in cvrisk() and changed plot.cvrisk()
bols: works now for factors and can be setup to use Ridgeestimation. Intercept can be omitted now (via center = TRUE).
new btree() baselearner for gamboost() available
fix inconsistencies in regression tests
add coef.gamboost
new generic
survFit
cosmetics for trace = TRUE
Changes in mboost version 1.01 (20071209)
inst/mboost_Bioinf.R was missing from mboost 1.00
Changes in mboost version 1.00 (20071113)
documentation updates
Changes in mboost version 0.90
tests update and release the new version on CRAN
predict(..., allIterations = TRUE) returns the matrix of predictors for all boosting iterations
Changes in mboost version 0.62
move mboost to Rforge
improvements in
gamboost
:Psplines as base learners available
new formula interface for specifying the base learner
new plot.gamboost
add the number of selected variables as degrees of freedom (as mentioned in the discussion of Hastie to Buehlmann & Hothorn)
status information during fitting is now available via boost_control(trace = TRUE) but is switched off by default
acknowledge contributions by Thomas Kneib and Matthias Schmid in DESCRIPTION
Changes in mboost version 0.61
gamboost() now allows for userspecified base learners via the formula interface
gamboost.matrix(x = x, ...) requires colnames being set for
x
na.action = na.omit fix for g{al}mboost()
Changes in mboost version 0.58 (20070531)
gamboost(..., weights = w) was broken
Changes in mboost version 0.57 (20070530)
extract response correctly in fitted.blackboost
hatvalues (and thus AICs) for GLMs with centering of covariates may have been wrong since version 0.50
add paper examples to tests
Changes in mboost version 0.56 (20070507)
fix Rd problems
Changes in mboost version 0.55 (20070425)

westbc
regenerated LazyLoad: yes (no SaveImage: yes)
Changes in mboost version 0.54 (20070418)
plot() method for
glmboost
objects visualizing the coefficient path (feature request by Axel Benner <benner@dkfz.de>).predict(newdata = <matrix>) was broken for gamboost(), thanks to Max Kuhn <Max.Kuhn@pfizer.com> for spotting this.
Changes in mboost version 0.53 (20070323)
predict() for gamboost(..., dfbase = 1) was not working correctly
small performance and memory improvements for glmboost()
Changes in mboost version 0.52 (20070228)
some performance improvements for
glmboost()
blackboost() is now generic with formula and x, y interface
plot() method for cvrisk() and AIC() output now allows for ylim specification without troubles
Changes in mboost version 0.51 (20070202)
depends party 0.99
Changes in mboost version 0.50 (20070130)
new
baselearner
argument togamboost
allowing to specify difference componentwise baselearners to be used. Currently implemented: "ssp" for smoothing splines (default), "bsp" for Bsplines and "ols" for linear models. The latter two haven't been tested yet.The
dfbase
arguments now applies to each covariate and no longer to each column of the design matrix.cvrisk() for blackboost() was broken, totally :(
centered covariates were returned by glmboost() and gamboost()
Poisson() used an incorrect offset
check for y being positive counts when family = "Poisson()"[B
checks for Poisson() logLik() and AIC() methods
fire a warning when all u > 0 or u < 0
update vignette ‘mboost_illustrations’
Changes in mboost version 0.417 (20070115)
fix problem with
dfbase
ingamboost
, spotted by Karin Eckel <Karin.Eckel@imbe.imed.unierlangen.de>
Changes in mboost version 0.416 (20070112)
work around stats4:::AIC
Changes in mboost version 0.415 (20061206)
fix plot problems in plot.cvrisk
allow for centering of the numerical covariates in glmboost and gamboost
Changes in mboost version 0.414 (20061027)
AIC(..., "classical") is now faster for nonGaussian families
Changes in mboost version 0.413 (20061004)
predict(..., newdata) can take a matrix now
Changes in mboost version 0.412 (20060913)
predict(<blackboostobject>, type = "response") did not return factors when the response was actually a factor
report offset in print methods
add offset attribute to coef.glmboost
Changes in mboost version 0.411 (20060907)
add
contrasts.arg
argument toglmboost.formula
more meaningful default for
grid
incvrisk
R2.4.0 fixes
Changes in mboost version 0.410 (20060830)
add checks for CoxPH (against coefficients and logLik of CoxPH)
add weights to CoxPH
the ngradient function in Family objects needs to implement arguments (y, f, w), not just (y, f)
check for meaningful class of the response for some families
Changes in mboost version 0.49 (20060717)
some small speed improvements in
gamboost
handle factors in
gamboost
properly (via a linear model)the dfbase argument can take a vector now (in
gamboost
)update and improve entries in DESCRIPTION
documentation updates
Changes in mboost version 0.48 (20060705)
Huber() is ‘Huber Error’, not ‘Huber Absolute Error’
added
CoxPH
family object for fitting Cox modelsremove inst/LaTeX
use NROW / NCOL more often (now that
y
may be aSurv
object)implement
cvrisk
, a general crossvalidation function for the empirical risk and a corresponding plot methodunify risk computations in all three fitting functions
unify names for
gb
objectsallow for outofbag risk computations
some cosmetics
update keywords in Rdfiles
risk was always 0 in Huber()@risk when d was chosen adaptively
pData(westbc)$nodal.y has levels
negative
andpositive
(lymph node status)
Changes in mboost version 0.47 (20060619)
add src/Makevars (required for Windows builds)
make sure objects that are modified at Clevel get _copied_ in
blackboost
Changes in mboost version 0.46 (20060614)
some minor
codetools
fixes: removed unused variables and an outdated functionadd
codetools
checks to regression testsfix xlab in plot.gbAIC

mboost version 0.45 published on CRAN 20060613