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 by mgcv::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: Set mc.preschedule = FALSE per default.
  • Added new option options(mboost_check_df2lambda = TRUE), which controls if a stability check in df2lambda is 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.


  • 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).


  • Fixed bug in PropOdds() which occurred if offset was specified: nuisance parameters delta and 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).