### R/`txshift`

*An R package for efficient estimation of and
nonparametric inference on the effects of stochastic intervention, including
in settings with multi-stage sampling designs. This provides a flexible way
to perform nonparametric variable importance analysis on continuous quantities
using the Targeted Learning
framework.*

View the package documentation and related information
*here*.

Joint work with David Benkeser.

[GitHub]

### R/`sl3`

*An R package providing a modern re-implementation
of the Super Learner algorithm for ensemble modeling and stacked regression
based on machine learning pipelines.*

View the package documentation and related information
*here*.

Joint work with Jeremy Coyle, Ivana
Malenica, and Oleg
Sofrygin.

[GitHub]

### R/`origami`

*An R package providing a general framework for
the application of various cross-validation schemes to arbitrary functions,
facilitating the extension of cross-validation procedures to numerous
applications.*

View the package documentation and related information
*here*.

Joint work with Jeremy Coyle.

[GitHub] |
[CRAN] |

### R/`hal9001`

*An R package providing a fast and efficient
implementation of the Highly Adaptive Lasso (HAL), a nonparametric regression
estimator with optimality guarantees.*

Joint work with Jeremy Coyle.

[GitHub]

### R/`survtmle`

*An R package providing facilities for estimation
and inference in right-censored survival analysis settings with and without
competing risks, including extensions for data-adaptive target parameters,
using Targeted Learning.*

View the package documentation and related information
*here*.

Joint work with David Benkeser.

[GitHub] |
[CRAN]

### R/`methyvim`

*An R package implementing a framework for using
Targeted Learning to assess evidence
for differential methylation across the genome by estimating variable
importance measures at the level of CpG sites and related functional
units.*

View the package documentation and related information
*here*.

Joint work with Mark van der
Laan and Alan
Hubbard.

[GitHub] |
[Bioconductor]

### R/`biotmle`

*An R package implementing a set of techniques
for discovering biomarkers from biological sequencing data using a
combination of Targeted Learning and a
generalization of moderated statistics for variance stabilization in finite
samples.*

View the package documentation and related information
*here*.

Joint work with Alan Hubbard.

[GitHub] |
[Bioconductor] |

### R/`adaptest`

*An R package for data-adaptive hypothesis testing
in high-dimensional settings. The approach allows for effects to be discovered
(“mined”) from data without loss of valid statistical inference using the
framework of Targeted Learning.*

Joint work with Weixin Cai and Alan
Hubbard.

[GitHub] |
[Bioconductor]

### R/`nima`

*An R package housing Nima’s personal R toolbox,
largely containing miscellaneous convenience functions written to make
statistical computing for research easier.*

View the package documentation and related information
*here*.

[GitHub] |
[CRAN]