Description Usage Arguments Value Author(s) See Also Examples

Recommend individualized treatment regime for future patients, based on the maximin projection learning method.

1 | ```
TR(object, x)
``` |

`object` |
Fitted object of class "MPL". |

`x` |
A matrix consisting of future patients baseline covariates. If there's only one group
of patients in the observed data fitted by "MPL", then future patients are assuming to coming from
this group and there is no restrictions on the number of observations in |

A vector of individualized treatments tailored for future patients.

Chengchun Shi

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
X <- matrix(rnorm(1600), 800, 2)
A <- rbinom(800, 1, 0.5)
h <- 1+sin(0.5*pi*X[,1]+0.5*pi*X[,2])
tau <- rep(0, 800)
B <- matrix(0, 2, 4)
B[,1] <- c(2,0)
B[,2] <- 2*c(cos(15*pi/180), sin(15*pi/180))
B[,3] <- 2*c(cos(70*pi/180), sin(70*pi/180))
B[,4] <- c(0,2)
for (g in 1:4){
tau[((g-1)*200+1):(g*200)] <- X[((g-1)*200+1):(g*200),]%*%B[,g]
}
## mean and scale of the subgroup covariates are allowed to be different
X[1:200,1] <- X[1:200,1]+1
X[201:400,2] <- 2*X[201:400,2]-1
X[601:800,] <- X[601:800,]/2
Y <- h+A*tau+0.5*rnorm(800)
G <- c(rep(1,200), rep(2,200), rep(3,200), rep(4,200))
result <- MPL(Y~X|A|G)
ITR <- TR(result, matrix(rnorm(200), 100, 2))
``` |

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