Description Usage Arguments Value References Examples

This function estimates the optimal Individualized Interval-valued Dose Rule (I2DR), and calculates a Wald-type confidence interval for the value function under the estimated optimal I2DR via Bootstrap.

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`Y` |
The patientâ€™s associated response/outcome, the larger the better by convention. |

`A` |
The dose level received by each patient, should be continuous. |

`X` |
The patientâ€™s baseline covariates, could be a matrix, including continous or discrete covariates. |

`cm` |
The constent cm in m=n/cm, where m is the number of total subinterval that diverges with sample size n. The default value is 6. |

`method` |
Two methods are available, Jump Q-learning ('JQL') and Residual Jump Q-learning ('RJQL'). The default method is 'JQL'. |

`Gamma.list` |
The candidate tuning paramter space for c1 in penalty term gamma=c1 log(n)/n. The default value is seq(from=1,to=20,by=2)/5. If the length of Gamma.list is 1, then the tuning process will be skipped. |

`Lambda.list` |
The candidate tuning paramter space for c2 in penalty term lambda=c2 log(n)/n. The default value is seq(from=1,to=20,by=2)/5. If the length of Lambda.list is 1, then the tuning process will be skipped. |

`RF_A.list` |
The candidate tuning paramter space for A in fitted E(Y|A=a,X) by Random Forest Regression for method 'RJQL' only. The default value is c(0,0.25,0.5,0.75,1). If the length of RF_A.list is 1, then the tuning process will be skipped. |

`folds_num` |
The number of the folds in the cross-validation process. The default value is 5. |

`alpha` |
The Confidence level. The default level is 0.95. |

`nboots` |
The number of Bootstrap. The default number is 500. |

An object of class "I2DR" which is a list with components:

`Partition` |
A partition of the entire dose range. |

`Beta` |
The regression coefficients for each partition. |

`Value` |
The estimated value function under our proposed I2DR. |

`low_bd` |
The lower bound of the confidence interval. |

`up_bd` |
The upper bound of the confidence interval. |

`method` |
The method used to find the I2DR. |

Jump Q-learning for Individualized Interval-valued Dose Rule.

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