103 lines
3.9 KiB
R
103 lines
3.9 KiB
R
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#'
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#' Create forest to compute difft
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#'
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#' \code{vt.forest} is a wrapper of \code{\link{VT.forest.one}},
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#' \code{\link{VT.forest.double}} and \code{\link{VT.forest.fold}}. With
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#' parameter forest.type, any of these class can be used with its own parameter.
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#'
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#' @param forest.type must be a character. "one" to use VT.forest.one class.
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#' "double" to use VT.forest.double. "fold" to use VT.forest.fold.
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#' @param vt.data \code{\link{VT.object}}. Can be return of \code{vt.data()}
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#' function
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#' @param interactions logical. If running VirtualTwins with treatment's
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#' interactions, set to TRUE (default value)
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#' @param method character c("absolute", "relative", "logit"). See
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#' \code{\link{VT.difft}}.
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#' @param model allows to give a model you build outside this function. Can be
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#' randomForest, train or cforest. Is only used with forest.type = "one". If
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#' NULL, a randomForest model is grown inside the function. NULL is default.
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#' @param model_trt0 works the same as model parameter. Is only used with
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#' forest.type = "double". If NULL, a randomForest model is grown inside the
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#' function. NULL is default. See \code{\link{VT.forest.double}} for details.
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#' @param model_trt1 see model_trt0 explanation and
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#' \code{\link{VT.forest.double}} details.
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#' @param fold number of fold you want to construct forest with k-fold method.
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#' Is only used with forest.type = "fold". Default to 5. See
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#' \code{\link{VT.forest.fold}}
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#' @param ratio numeric value that allow sampsize to be a bit controlled.
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#' Default to 1. See \code{\link{VT.forest.fold}}.
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#' @param ... randomForest() function parameters. Can be used for any forest.type.
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#'
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#' @return \code{VT.difft}
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#'
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#' @examples
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#'
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#' data(sepsis)
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#' vt.o <- vt.data(sepsis, "survival", "THERAPY", T)
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#' # inside model :
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#' vt.f <- vt.forest("one", vt.o)
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#' # ...
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#' # your model :
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#' # library(randomForest)
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#' # rf <- randomForest(y = vt.o$getY(),
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#' # x = vt.o$getX(int = T),
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#' # mtry = 3,
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#' # nodesize = 15)
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#' # vt.f <- vt.forest("one", vt.o, model = rf)
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#' # ...
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#' # Can also use ... parameters
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#' vt.f <- vt.forest("one", vt.o, mtry = 3, nodesize = 15)
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#' # ...
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#'
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#'
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#' @include forest.R difft.R
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#'
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#' @name vt.forest
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#'
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#' @export vt.forest
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vt.forest <- function(forest.type = "one", vt.data, interactions = T, method = "absolute",
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model = NULL, model_trt1 = NULL, model_trt0 = NULL, ratio = 1, fold = 10, ...){
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if(!inherits(vt.data, "VT.object"))
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stop("vt.data must be VT.object class")
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params <- list(...)
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if (forest.type == "one"){
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if(is.null(model)){
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model <- randomForest::randomForest(x = vt.data$getX(interactions = interactions, trt = NULL),
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y = vt.data$getY(),
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...)
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}
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rf <- model
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vt.difft <- VT.forest.one(vt.object = vt.data, model = rf, interactions = interactions, method = method)
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} else if (forest.type == "double"){
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if(is.null(model_trt1)){
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model_trt1 <- randomForest::randomForest(x = vt.data$getX(trt = 1),
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y = vt.data$getY(1),
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...)
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}
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rf_trt1 <- model_trt1
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if(is.null(model_trt0)){
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model_trt0 <- randomForest::randomForest(x = vt.data$getX(trt = 0),
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y = vt.data$getY(0),
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...)
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}
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rf_trt0 <- model_trt0
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vt.difft <- VT.forest.double(vt.object = vt.data, model_trt1 = rf_trt1, model_trt0 = rf_trt0, method = method)
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} else if (forest.type == "fold"){
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vt.difft <- VT.forest.fold(vt.object = vt.data, fold = fold, ratio = ratio,
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interactions = interactions, method = method)
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} else
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stop("forest.type must be one, double or fold")
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if(forest.type %in% c("one", "double"))
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vt.difft$run()
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else
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vt.difft$run(...)
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return(vt.difft)
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}
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