Dynamic Reinforcement Learning and Adaptive Progressive Censoring


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Documentation for package ‘DRLAP2’ version 0.1.1

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calc_reward Calculate Reward Signal
compute_drl_sums_cpp Compute DRL Sums (C++)
drl_log_target_beta_cpp Compute Log Target Density for Beta (C++)
fit_drl_bayes Bayesian MCMC Sampler for DRL-AP2 Weibull Model
fit_drl_mle Maximum Likelihood Estimation for DRL-AP2 Weibull Model (C++ Accelerated)
init_drl_env Initialize MDP State Observer for Dynamic Censoring