A functional programming based
implementation of the super learner algorithm with an emphasis on supporting
the use of formulas to specify learners. This approach offers several
improvements compared to past implementations including the ability to
easily use random-effects specified in formulas
(like y ~ (age | strata) + ...) and construction of new learners is
as simple as writing and passing a new function. The
super learner algorithm was originally described in van der Laan et al.
(2007) <https://biostats.bepress.com/ucbbiostat/paper222/>.
| Version: |
0.0.1 |
| Depends: |
R (≥ 4.2.0) |
| Imports: |
dplyr, earth, future, future.apply, gbm, glmnet, hal9001, lifecycle, lme4, methods, mgcv, nnet, nnls, origami, randomForest, ranger, tibble, tidyr, VGAM, xgboost |
| Suggests: |
MASS, ggplot2, knitr, palmerpenguins, rmarkdown, survival, testthat (≥ 3.0.0), withr |
| Published: |
2026-02-20 |
| DOI: |
10.32614/CRAN.package.nadir |
| Author: |
Christian Testa 
[aut, cre],
Nima Hejazi [ths,
aut] |
| Maintainer: |
Christian Testa <ctesta at hsph.harvard.edu> |
| BugReports: |
https://github.com/ctesta01/nadir/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://ctesta01.github.io/nadir/,
https://github.com/ctesta01/nadir/ |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
nadir results |