CRAN/E | DynTxRegime

DynTxRegime

Methods for Estimating Optimal Dynamic Treatment Regimes

Installation

About

Methods to estimate dynamic treatment regimes using Interactive Q-Learning, Q-Learning, weighted learning, and value-search methods based on Augmented Inverse Probability Weighted Estimators and Inverse Probability Weighted Estimators. Dynamic Treatment Regimes: Statistical Methods for Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and Laber, E. B., Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8.

Key Metrics

Version 4.15
Published 2023-11-24 153 days ago
Needs compilation? no
License GPL-2
CRAN checks DynTxRegime results

Downloads

Yesterday 20 0%
Last 7 days 131 -22%
Last 30 days 506 +12%
Last 90 days 1.431 -23%
Last 365 days 6.313 -3%

Maintainer

Maintainer

Shannon T. Holloway

shannon.t.holloway@gmail.com

Authors

S. T. Holloway
E. B. Laber
K. A. Linn
B. Zhang
M. Davidian
A. A. Tsiatis

Material

NEWS
Reference manual
Package source

In Views

CausalInference

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

DynTxRegime archive

Depends

methods
modelObj
stats

Imports

kernlab
rgenoud
dfoptim

Suggests

MASS
rpart
nnet

Reverse Imports

DevTreatRules
polle