78 lines
2.6 KiB
R
78 lines
2.6 KiB
R
# VT.FOREST.DOUBLE --------------------------------------------------------
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# IF RUNNING DOUBLE FOREST COMPUTATION
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#' Difft by double random forest
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#'
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#' A reference class to compute twins via double random forests
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#'
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#' \code{VT.forest.double} extends \code{VT.forest}.
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#'
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#' \eqn{E(Y|T = 1)} if \eqn{T_i = 1} is estimated by OOB predictions from
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#' \code{model_trt1}.
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#' \eqn{E(Y|T = 0)} if \eqn{T_i = 0} is estimated by OOB predictions from
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#' \code{model_trt0}.
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#' This is what \code{computeTwin1()} does.
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#'
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#' Then \eqn{E(Y|T = 1)} if \eqn{T_i = 0} is estimated by model_trt1.
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#' Then \eqn{E(Y|T = 0)} if \eqn{T_i = 1} is estimated by model_trt1.
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#' This is what \code{computeTwin2()} does.
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#'
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#' @include forest.R
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#'
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#' @field model_trt1 a caret/RandomForest/randomForest object for treatment T =
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#' 1
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#' @field model_trt0 a caret/RandomForest/randomForest object for treatment T =
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#' 0
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#' @field ... field from parent class : \code{\link{VT.forest}}
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#'
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#' @seealso \code{\link{VT.difft}}, \code{\link{VT.forest}},
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#' \code{\link{VT.forest.one}}
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#'
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#' @export VT.forest.double
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#'
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#' @name VT.forest.double
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#'
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#' @import methods
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VT.forest.double <- setRefClass(
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Class = "VT.forest.double",
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contains = "VT.forest",
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fields = list(
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model_trt1 = "ANY",
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model_trt0 = "ANY"
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),
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methods = list(
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initialize = function(vt.object, model_trt1, model_trt0, ...){
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.self$checkModel(model_trt1)
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.self$checkModel(model_trt0)
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.self$model_trt1 <- model_trt1
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.self$model_trt0 <- model_trt0
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callSuper(vt.object, ...)
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},
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computeTwin1 = function(){
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"Compute twin1 with OOB predictions from double forests. See details."
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# Model with treatment (1)
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.self$twin1[.self$vt.object$data[, 2] == 1] <- VT.predict(rfor = .self$model_trt1, type = .self$vt.object$type)
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# Model without treatment (0)
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.self$twin1[vt.object$data[, 2] == 0] <- VT.predict(rfor = .self$model_trt0, type = .self$vt.object$type)
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return(.self$twin1)
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return(invisible(.self$twin1))
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},
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computeTwin2 = function(){
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"Compute twin2 by the other part of data in the other forest. See details."
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# Model with treatment (1)
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.self$twin2[.self$vt.object$data[, 2] == 1] <- VT.predict(.self$model_trt0, newdata = .self$vt.object$getX(1, interactions = F), type = .self$vt.object$type)
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# Model without treatment (0)
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.self$twin2[.self$vt.object$data[, 2] == 0] <- VT.predict(.self$model_trt1, newdata = .self$vt.object$getX(0, interactions = F), type = .self$vt.object$type)
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return(invisible(.self$twin2))
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}
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)
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) |