context("rackauskas_zuokas works for two lm examples across all argument permutations")
# theargs <- formals(rackauskas_zuokas)
test_that("linear regression works with all combinations of formals (data)", {
carslm <- lm(dist ~ speed, data = cars)
bostonlm <- lm(medv ~ crim + zn + indus + chas + nox + rm +
age + dis + rad + tax + ptratio + b + lstat, data = BostonHousing)
theargs <- list("alpha" = c(0, 15 / 32), "pvalmethod" = c("data"),
"R" = 2 ^ 14, "m" = 2 ^ 17, "sqZ" = c(TRUE, FALSE),
"mainlm" = list(carslm, bostonlm))
allargs <- expand.grid(theargs, stringsAsFactors = FALSE)
pvals <- vapply(1:nrow(allargs), function(i) do.call(what = rackauskas_zuokas,
args = append(list("statonly" = FALSE, "seed" = 1234),
unlist(allargs[i, ], recursive = FALSE)))$p.value, NA_real_)
lapply(1:length(pvals), function(i) expect_true(is.btwn01(pvals[i])))
})
test_that("linear regression works with all combinations of formals (sim)", {
skip_on_cran()
carslm <- lm(dist ~ speed, data = cars)
bostonlm <- lm(medv ~ crim + zn + indus + chas + nox + rm +
age + dis + rad + tax + ptratio + b + lstat, data = BostonHousing)
theargs <- list("alpha" = c(0, 15 / 32), "pvalmethod" = c("sim"),
"R" = 2 ^ 14, "m" = 2 ^ 4, "sqZ" = c(TRUE, FALSE),
"mainlm" = list(carslm, bostonlm))
allargs2 <- expand.grid(theargs, stringsAsFactors = FALSE)
pvals2 <- vapply(1:nrow(allargs2), function(i) do.call(what = rackauskas_zuokas,
args = append(list("statonly" = FALSE, "seed" = 1234),
unlist(allargs2[i, ], recursive = FALSE)))$p.value, NA_real_)
lapply(1:length(pvals2), function(i) expect_true(is.btwn01(pvals2[i])))
})
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