qLearn: Estimation and inference for Q-learning

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Functions to implement Q-learning for estimating optimal dynamic treatment regimes from two stage sequentially randomized trials, and to perform inference via m-out-of-n bootstrap for parameters indexing the optimal regime.

Author
Jingyi Xin, Bibhas Chakraborty, and Eric B. Laber
Date of publication
2012-03-09 10:12:37
Maintainer
Bibhas Chakraborty <bc2425@columbia.edu>
License
GPL-2
Version
1.0

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Man pages

chooseMDoubleBootstrap
Choose the bootstrap sample size for stage 1 inference
getModel
Compute the regression coefficients for both stages
qLearn
Based on the input contrast vectors, compute point estimates...

Files in this package

qLearn
qLearn/MD5
qLearn/R
qLearn/R/qLearn.R
qLearn/R/getModel.R
qLearn/R/chooseMDoubleBootstrap.R
qLearn/NAMESPACE
qLearn/man
qLearn/man/qLearn.Rd
qLearn/man/getModel.Rd
qLearn/man/chooseMDoubleBootstrap.Rd
qLearn/DESCRIPTION