compute_rl_scenarios {RLescalation}R Documentation

Compute DLT Probability Scenarios for Reinforcement Learning

Description

Compute the scenarios described in Sect. 2.2 of the original paper.

Usage

compute_rl_scenarios(J, target, epsilon, delta, lower = 0.1, upper = 0.8)

Arguments

J

A positive integer value. The number of doses.

target

A positive numeric value. The target DLT probability.

epsilon

A positive numeric value. The acceptable range of target DLT probabilities is defined as [target - epsilon, target + epsilon].

delta

A positive numeric value. The unacceptable ranges of target DLT probabilities are defined as [0, target - delta] and [target + delta, 1].

lower

A positive numeric value. Values lower than lower are clipped. Default is 0.1, which is modified from Sect. 2.2 of the original paper.

upper

A positive numeric value. Values higher than upper are clipped. Default is 0.8.

Value

A named list of three elements: - prob: a list of DLT probability scenarios - MTD: a list of true MTD indices (Note that -1 means "no MTD") - weight: a vector of weights for each scenario

Examples

scenarios <- compute_rl_scenarios(J = 6, target = 0.25, epsilon = 0.04, delta = 0.1)
print(scenarios)


[Package RLescalation version 1.0.2 Index]