tramnet

• New model.matrix() method.
• mbo_recommended() additionally accepts a fitted "tramnet" object.
• Case weights and offsets are now taken into account when fitting.

Changes

• Model-based optimization now uses package 'mlr3mbo' instead of the retired package 'mlrMBO'. Function names and arguments of mbo_tramnet(), elnet_obj(), lasso_obj(), ridge_obj() and mbo_recommended() are unchanged, but the default of opt_crit is now "ei", mbo_tramnet() returns a list and the objective functions are of class bbotk::ObjectiveRFun.
• Tests use 'testthat'.
• Removed unused dependencies ('mlbench', 'utils') and the unused internal function .plot_cvl(). The package description no longer mentions models for binary and ordered categorical responses, which cannot be fitted.

Bug fixes

• logLik(object, newdata) now returns the out-of-sample log-likelihood without subtracting the penalty of the training fit. Consequently, cvl_tramnet() and mbo_tramnet() tune lambda and alpha based on the unpenalized out-of-sample log-likelihood (log score), which previously favoured small values of lambda.
• The quadratic part of the penalty was erroneously scaled by lambda^2 instead of lambda in the objective function. The penalty is now lambda * (0.5 * (1 - alpha) * ||beta||_2^2 + alpha * ||beta||_1), as documented and as in 'glmnet', and coincides with the penalty subtracted in logLik(). Fits with alpha < 1 and lambda different from 0 and 1 change.
• predict(), simulate(), plot(), residuals() and estfun() now use the correct sign of the shift term for models with negative = TRUE, such as Lm(), BoxCox(), Lehmann() and Survreg().
• plot_path() no longer warns when restoring graphical parameters.
• predict(), simulate() and plot() work with non-syntactic column names of the design matrix (e.g., interactions or log(x)).
• prof_lambda(), prof_alpha() and cvl_tramnet(..., fit_opt = TRUE) refit models directly instead of re-evaluating the original call, which failed when the baseline model or the design matrix were not visible from the global environment.