FEATURES / CHANGES
coef.glmnetLRC()
receieves a tolerance argument to avoid selecting coefficients that are very close to 0.
FIXES
predict.glmnetLRC()
now correctly handles matrices as predictors, as well as data frames.
FEATURES / CHANGES
- Removing use of
Smisc::sortDF()
insingle_glmnetLRC()
FEATURES / CHANGES
- Added
plot.LRCpred()
to plot the predicted probabilites of the LRC, along with associated tests - In
summary.LRCpred()
: Included summary of predicted probabilities, addedprint.summaryLRCpred()
- Tightened up the argument checking of
predLoss_glmnetLRC()
FEATURES / CHANGES
- Added prediction probabilities to the output of the
predict.glmnetLRC()
method
FIXES
- Corrected the way
predict.glmnetLRC()
handled additional columns specified bykeepCols
FEATURES / CHANGES
- Added the
missingpreds
methods to easily identify needed predictors that may not be present in new data - Remove uneeded documentation for generic method,
extract
FEATURES / CHANGES
- Package vignette moved to online docs
- Minor documentation edits
FEATURES / CHANGES
- Addition of tests against manual fitting with standardized predictors
FEATURES / CHANGES
- Original package deployment to github