# opt.dose: Optimal Interval-valued Dose under the Individualized... In JQL: Jump Q-Learning for Individualized Interval-Valued Dose Rule

## Description

This function assigns each individual to one of the subintervals of the entire dosage according to his/her baseline covariates under the estimated I2DR.

## Usage

 `1` ``` opt.dose(X,I2DR) ```

## Arguments

 `X` The patient’s baseline covariates, coule be a matrix, including continous or discrete covariates. `I2DR` The Individualized Interval-valued Dose Rule found by the function "JQL" or "RJQL".

## Value

 `opt.dose` The optimal Interval-valued dosage for each individual.

## References

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

## Examples

 ```1 2 3 4 5 6 7 8 9``` ```n=50 d=4 x=matrix(runif(n*(d-1),-1,1),nrow=n,ncol=d-1) a=runif(n,0,1) y=(1+x[,1])*(a>=0&a<0.35)+(x[,1]-x[,2])*(a>=0.35&a<0.65)+(1-x[,2])*(a>=0.65&a<=1)+rnorm(n,0,1) rule=find.I2DR(Y=y,A=a,X=x) n0=10 xnew=matrix(runif(n0*(d-1),-1,1),nrow=n0,ncol=d-1) opt.dose(X=xnew,I2DR=rule) ```

JQL documentation built on Nov. 16, 2019, 1:07 a.m.