Performance enhancements - Faster (correct) test for number of candidate values in node splitting. - Remove lock on log gamma (beta splitting rule).
Bug-fixes - Fix container overrun and incorrect (unweighted) sampling without replacement.
Documentation fixes - Incorrect spelling of Breiman and missing reference in README - Added github links
This is the initial release of literanger, a refactoring and adaptation of the ranger package https://github.com/imbs-hl/ranger for random forests. The purpose of this update was to refactor the prediction code to enable efficient prediction when embedded into the multiple imputation algorithm proposed by Doove et al in:
Doove, L. L., Van Buuren, S., & Dusseldorp, E. (2014). Recursive partitioning for missing data imputation in the presence of interaction effects. Computational statistics & data analysis, 72, 92-104.
Currently supports: - Classification and regression trees/forests. - Prediction types: - Conventional ‘bagged’ prediction (most frequent value or mean). - Terminal node identifiers for all trees. - Prediction given by drawing a tree for each prediction and then drawing an in-bag value from the terminal node.