Nothing
test_that("Test different resampling approaches (continuous)", {
skip_on_cran()
## Continuous ##
dat_ctns = generate_subgrp_data(family="gaussian")
Y = dat_ctns$Y
X = dat_ctns$X
A = dat_ctns$A
# ### Bootstrap ###
res0 <- PRISM(Y, A, X, ple="None", param="lm", resample="Bootstrap", R=50)
test0 = ifelse( is.null(res0$resamp_dist), 0, 1)
### Cross-Validation ###
res1 <- PRISM(Y, A, X, ple="None", param="lm", resample="CV")
test1 = ifelse( is.null(res1$resamp_dist), 0, 1)
tests_ctns = ifelse( sum(test0,test1)==2, 1, 0)
### Output Test Results ###
expect_equal(tests_ctns, 1L)
})
test_that("Test different resampling approaches (survival)", {
skip_on_cran()
### Survival Tests ###
library(survival)
require(TH.data); require(coin)
data("GBSG2", package = "TH.data")
surv.dat = GBSG2
# Design Matrices ###
Y = with(surv.dat, Surv(time, cens))
X = surv.dat[,!(colnames(surv.dat) %in% c("time", "cens")) ]
set.seed(513)
A = rbinom( n = dim(X)[1], size=1, prob=0.5 )
### Bootstrap ###
res0 <- PRISM(Y, A, X, resample="Bootstrap", R=50, ple="None")
test0 = ifelse( is.null(res0$resamp_dist), 0, 1)
### Cross-Validation ###
res1 <- PRISM(Y, A, X, resample="CV", ple="None")
test1 = ifelse( is.null(res1$resamp_dist), 0, 1)
tests_surv = ifelse( sum(test0,test1)==2, 1, 0)
### Output Test Results ###
expect_equal(tests_surv, 1L)
})
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