btree(..., by = ) caused problems when restricting the number of boosting iterations.
Miscellaneous
Speed-up vignettes.
Use less precision in numerical vignette outputs.
Changes in mboost version 2.9-4 (2020-12-09)
User-visible changes
New maintainer: Torsten Hothorn follows Benjamin Hofner, who curated the 2.6-2.9 series, as maintainer. All authors thank Benny for 4 years of package maintainance!
Added by argument to btree; only binary factors are allowed.
Bug-fixes
Add missing rclass function to derive class predictions from conditional class probabilities to Binomial() family.
Plot correct x-axis in plot(cvrisk(...))(closes #102).
Changes in mboost version 2.9-3 (2020-08-06)
Bug-fixes
Removed deprecated argument LINPACK from all calls to solve. Fixes #109.
Added family RCG for ratio of correlated gammas and downstream test, see Weinhold et al. (2016). Closes #86.
Removed corrected cross-validation for Cox models (Verweij and van Houwelingen, 1993) as it was not working. Closes #85.
Use partykit::ctree instead of party::ctree inbtree and blackboost. 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 or grid in stabsel.
Allow leave-one-out crossvalidation (via type = "kfold").
Bug-fixes
Throw error when data is not compatibel (instead of silently recycling the vector). Fixes #79.
Fixed handling of offset for families NBinomial and Hurdle. Closes #88.
Replace cBind (now deprecated) with cbind. Fixes #90.
Fix predict with zero iterations (names were not correctly assigned). Fixes #87.
Fixed labels in plot function for categorical base-learners.
Miscellaneous
Added further tests / checks.
Removed unused functions (response) and arguments (bnames from extract.glmboost).
Update email address and added ORCIDs.
Changes in mboost version 2.8-1 (2017-07-19)
User-visible changes
Added all possible options to the specific boosting functions instead of passing the options via ... to mboost_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.
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.
Bug-fixes
Fix handling of missing values in mboost and gamboostwhen weights are specified. Fixes #80.
Changes in mboost version 2.8-0 (2017-05-04)
User-visible changes
Models with zero steps (i.e., models containing only the offset) can now be fitted. Furthermore, cross-validation can now also select a model without base-learners. Fixes #64, #66, and #69.
Binomial now uses link functions by making use of make.link. Furthermore, an alternative implementation of Binomial models along the lines of the glm implementation can be used via Binomial(type = "glm"). Additionally, it works not only with a two-level factor but also with a two-column matrix containing the number of successes and number of failures. Fixes #34, #63 and#65.
Added new base-learner bkernel for kernel boosting as described in S. Friedrichs, J. Manitz, P. Burger, C.I. Amos, A. Risch, J.C. Chang-Claude, H.E. Wichmann, T. Kneib, H. Bickeboeller, and B. Hofner (2017), Pathway-Based Kernel Boosting for the Analysis of Genome-Wide Association Studies.Computational and Mathematical Methods in Medicine. 2017(6742763), 1-17. doi:10.1155/2017/6742763.
Removed check if df2lambda is stable. Hence, options(mboost_check_df2lambda) (introduced in mboost 2.5-0) 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, 106:494-510. (see system.file("India_quantiles.R", package = "mboost"))
Fixed package citation.
Register C routines to make CRAN happy (again). Fixes #77.
Bug-fixes
Make sure that family = Multinomial is only used with Kronecker product base-learners. Fixes #46.
If center is specified as boolean value in bols, 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 in fitted. Fixes #76.
Changes in mboost version 2.7-0 (2016-11-23)
User-visible 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 multiple levelplots, i.e., maps (thanks to Mikko Korpela). See pull request #39.
Provide sensible defaults for xlab and ylab and allow user-specified axis labels for bi- and multivariate plots. Fixes #51.
Export plot functions (plot.glmboost, plot.mboost, lines.mboost, plot.varimp and plot.cvrisk) for better usability and visibility.
Miscellaneous
Updated manual regarding the usage of families and clarified the usage of argument qoffset.
Updated manual for base-learners:
Highlight that x should be centered if bols(x, intercept = FALSE)is used.
Discourage using bbs(, constraint != "none"); Preferably use bmono for constrained effect estimates. Fixes #36.
Improved vignettes (thanks to Mikko Korpela). See pull request #38.
Bug-fixes
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 2.6-0 (2016-03-11)
User-visible 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 asboost-R/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 when length(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. Usemboost_intern() instead. Caution: Do not use this function.
Bug-fixes
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 2.5-0 (2015-08-13)
User-visible changes
Added documentation for plot.mboost function and moved documentation of plot.glmboost to the same help page. Resolves issue #14.
bbs and bmono no longer allow data outside of the boundary.knots during model fitting.
Predictions for bbs and bmono 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 a warning 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 in df2lambdais performed. If set to FALSE this might speed up the computation of df2lambda 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 df2lambdaas the singular values are sufficient and as “computing the singular vectors is the slow part for large matrices” (proposed by Fabian Scheipl).
Bug-fixes
Fixed bug in PropOdds() which occurred ifoffset was specified: nuisance parameters deltaand sigma 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 that A is symmetric if it is Matrix-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 2.4-2 (2015-02-12)
User-visible changes
Export df2lambda, hyper_bbs and bl_linto make package FDboost happy. Note: These functions usually should not be called directly by users.
Miscellaneous
Added Hothorn et al (2010) to ‘inst/CITATION’
Bug-fixes
Changes in ‘inst/CITATION’ to make CRAN happy: Citations can now be extracted without the need to install the package.
Removed EISPACK = FALSE from eigen() as the argument is defunct and ignored.
Changed require to requireNamespace
Changes in mboost version 2.4-1 (2014-12-15)
Miscellaneous
Moved generic definition of selected to stabswhich is required anyway (thus, stabs >= 0.5-0 is now required)
load AML dataset (‘AML_Bullinger.rda’) from packageTH.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.
Bug-fixes
Cross-validation was potentially wrong for CoxPH()models. Users can now choose if they want the naive cross-validation or the improved version by Verweij and van Houwelingen (1993); (spotted by Holger Reulen <hreulen _ at _ uni-goettingen.de>)
Examples in \dontrun are now executable and all dependencies are properly stated in ‘DESCRIPTION’
Changes in mboost version 2.4-0 (2014-10-02)
User-visible changes
Added confint function to compute (bootstrap) confidence intervals together with plot and print methods
stabsel() now depends on the new package stabswhere the back end and methods such as plot andprint are implemented
Improved plot method for varying coefficients (ylim now suitable) and base-learners of factor variables.
Tweaked update function: we now can turn thetrace on and off, and specify the type of risk as well as the oobweight to update()
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 use party::ctree_control etc.
Bug-fixes
glmboost()$model.frame() was broken
glmboost()$update() was broken
predict() for models with non-scalar offsets was broken
Changes in mboost version 2.3-0 (2014-06-26)
User-visible 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 P-splines (type = "quad.prog")
new constraints added for positive and negative spline estimates
bbs
allows monotone T-splines (experimental)
new argument deriv to bbs for computing derivatives of B-splines
bmrf can now also handle neighborhood matrices as an argument to bnd
added new families Hurdle and Multinomial
boost_control: added new argument stopintern 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 to variable.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
Bug-fixes
fixed a problem with extract() of single base-learners
fixed bug in AIC.mboost: df = "actset" can only be used with glmboost models
fixed package start up messages
fixed a problem in mboost_fit (when names of base-learners were missing)
Changes in mboost version 2.2-3 (2013-09-09)
fixed bugs in survival families:
offset in all survival families was based onmax(survtime) instead of max(log(survtime));
offset in CoxPH can't be computed from Cox Partial LH as constants are canceled out; Use fixed offsetinstead;
speed up checking of manual by changing some computations (e.g. reducemstop) or exclude code from checking via \dontrun{}
removed dependency on ipred (replaced with TH.data)
small improvements in manual
Changes in mboost version 2.2-2 (2013-02-08)
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 default bols(x) + bbs(x, center = TRUE) or, equivalently,bols(x) + bbs(x, center = "differenceMatrix"). For bbs(x, y, center = TRUE) or bmrf(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 for mclapply
fixed bug in brandom: now really usecontrasts.arg = "contr.dummy" per default.
removed tests/ folder and .Rout.save files for vignettes from the CRAN release
small improvements in manual
Changes in mboost version 2.2-1 (2013-01-14)
included warnings in stabsel() for better guidance of the user:
A warning is issued if the upper bound for theFWER 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 base-learners to reflect the change in the default for degrees of freedom (additionally, all options are now discussed in a separate section of the base-learner 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)) statements
changed start up message
Changes in mboost version 2.2-0 (2012-11-21)
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") to FALSE, 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 B-spline 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) P-splines
[experimental] added family Gehan() for rank-based estimation of survival models in an accelerated failure time framework (contributed by Brent Johnson bajohn3@emory.edu)
Changes in mboost version 2.1-3 (2012-09-27)
matrices with one column are now handled as vectors in base-learners
improved manual
fixed error that occurs with R (>= 2.16) due to internal changes in R
Changes in mboost version 2.1-2 (2012-02-29)
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 2.1-1 (2011-11-28)
new option "mboost_eps" for factor in Demmler-Reinsch orthogonalization
Changes in mboost version 2.1-0 (2011-11-15)
Base-learners
added base-learners for smooth monotonic (or convex/concave) functions of one or two variables (bmono())
added base-learners for radial basis functions (brad())
added base-learners 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 base-learners (although not yet exported and not via the formula interface)
new experimental base-learner %O% for smoothing matrix-values 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 base-learners 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 base-learners (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: out-of-bag-risk 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 base-learners that are combined via %+%.
various improvements and fixes in manuals
Changes in mboost version 2.0-12 (2011-08-22)
minor bug-fixes 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 2.0-11 (2011-03-17)
fix problem in bl_lin when using dense matrices from package "Matrix"
Changes in mboost version 2.0-10 (2011-02-20)
add rqss results for India childhood malnutrition data
Changes in mboost version 2.0-9 (2010-11-19)
add gbm to Suggests
Changes in mboost version 2.0-8 (2010-11-11)
make survival package happy again
Changes in mboost version 2.0-7 (2010-09-28)
vignette "mboost" updated
remove problem with R CMD check that occurred on some 64bit systems
Changes in mboost version 2.0-6 (2010-05-22)
no not use multicore functionality in R CMD check, really.
Changes in mboost version 2.0-5 (2010-05-21)
no not use multicore functionality in R CMD check
Changes in mboost version 2.0-4 (2010-04-15)
new vignette "mboost" describing 2.0-x 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 2.0-3 (2010-03-10)
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 2.0-2 (2010-03-04)
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 0.9-9993)
Changes in mboost version 2.0-1 (2010-03-01)
fixed bug in coef( , aggregate = "cumsum"): fraction "nu" was missing
Changes in mboost version 2.0-0 (2010-02-01)
generic implementation of component-wise functional gradient boosting in mboost_fit, specialized code for linear, additive and interaction models removed
new 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 base-learners (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 plot-function. Users can specify "which" as numeric value or as a character string
added function cv() to generate matrices for k-fold cross-validation, 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 base-learners replaced with "by"
bns and bss deprecated;
Changes in mboost version 1.1-4 (2009-11-18)
fixed bug in prediction with varying coefficients for binary effect modifiers
Changes in mboost version 1.1-3 (2009-09-21)
better x-axes 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 1.1-2 (2009-07-21)
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 1.1-1 (2009-04-21)
new quantile regression facilities.
fix problem with bbs base-learner and cvrisk
Changes in mboost version 1.1-0 (2009-03-27)
bbs instead of bss is the default base-learner in gamboost
make sure bbs with weights and expanded observations returns numerically the very same results
negative gradient of GaussClass() was wrong, spotted by Kao Lin linkao@picb.ac.cn
Changes in mboost version 1.0-3 (2008-11-07)
Date was malformed in DESCRIPTION
Changes in mboost version 1.0-2 (2008-11-05)
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 set-up to use Ridge-estimation. Intercept can be omitted now (via center = TRUE).
new btree() base-learner for gamboost() available
fix inconsistencies in regression tests
add coef.gamboost
new generic survFit
cosmetics for trace = TRUE
Changes in mboost version 1.0-1 (2007-12-09)
inst/mboost_Bioinf.R was missing from mboost 1.0-0
Changes in mboost version 1.0-0 (2007-11-13)
documentation updates
Changes in mboost version 0.9-0
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 0.6-2
move mboost to R-forge
improvements in gamboost:
P-splines 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 0.6-1
gamboost() now allows for user-specified 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 0.5-8 (2007-05-31)
gamboost(..., weights = w) was broken
Changes in mboost version 0.5-7 (2007-05-30)
extract response correctly in fitted.blackboost
hatvalues (and thus AICs) for GLMs with centering of covariates may have been wrong since version 0.5-0
add paper examples to tests
Changes in mboost version 0.5-6 (2007-05-07)
fix Rd problems
Changes in mboost version 0.5-5 (2007-04-25)
westbc regenerated
LazyLoad: yes (no SaveImage: yes)
Changes in mboost version 0.5-4 (2007-04-18)
plot() method for glmboost objects visualizing the coefficient path (feature request by Axel Benner benner@dkfz.de).
predict(newdata = ) was broken for gamboost(), thanks to Max Kuhn Max.Kuhn@pfizer.com for spotting this.
Changes in mboost version 0.5-3 (2007-03-23)
predict() for gamboost(..., dfbase = 1) was not working correctly
small performance and memory improvements for glmboost()
Changes in mboost version 0.5-2 (2007-02-28)
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 0.5-1 (2007-02-02)
depends party 0.9-9
Changes in mboost version 0.5-0 (2007-01-30)
new baselearner argument to gamboost allowing to specify difference component-wise base-learners to be used. Currently implemented: "ssp" for smoothing splines (default), "bsp" for B-splines 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