DESCRIPTION

Package: RLescalation
Type: Package
Title: Optimal Dose Escalation Using Deep Reinforcement Learning
Version: 1.0.1
Authors@R: c(
    person("Kentaro", "Matsuura", , "matsuurakentaro55@gmail.com", 
           role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0001-5262-055X")))
Description: An implementation to compute an optimal dose escalation rule
    using deep reinforcement learning in phase I oncology trials
    (Matsuura et al. (2023) <doi:10.1080/10543406.2023.2170402>).
    The dose escalation rule can directly optimize the percentages of correct
    selection (PCS) of the maximum tolerated dose (MTD).
URL: https://github.com/MatsuuraKentaro/RLescalation
BugReports: https://github.com/MatsuuraKentaro/RLescalation/issues
VignetteBuilder: knitr
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
Imports: 
    glue,
    R6,
    nleqslv,
    reticulate,
    stats,
    utils
Suggests:
    knitr,
    rmarkdown
Collate:
    'timer.R'
    'train_algo.R'
    'utils.R'
    'escalation_rule.R'
    'rl_dnn_config.R'
    'rl_config_set.R'
    'compute_rl_scenarios.R'
    'learn_escalation_rule.R'
    'setup_python.R'
    'zzz.R'
    'simulate_one_trial.R'