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jan-imbi committed Jul 10, 2024
1 parent 061a1a5 commit 9af21aa
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2 changes: 1 addition & 1 deletion DESCRIPTION
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@@ -1,7 +1,7 @@
Package: adestr
Type: Package
Title: Estimation in Optimal Adaptive Two-Stage Designs
Version: 0.5.2
Version: 1.0.0
Authors@R:c(person("Jan", "Meis", role = c("aut", "cre"), email = "meis@imbi.uni-heidelberg.de", comment = c(ORCID = "0000-0001-5407-7220")),
person("Martin", "Maechler", role = c("cph"), email = "maechler@stat.math.ethz.ch", comment = c(ORCID = "0000-0002-8685-9910", "Original author of monoSpl.c (from the 'stats' package).")))
Description:
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1 change: 1 addition & 0 deletions tests/testthat/test_densities.R
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Expand Up @@ -212,6 +212,7 @@ test_that("two-armed trial, full sampling distribution, unknown variance, integr

test_that("two-armed trial, full sampling distribution, unknown variance, integral of second-stage density equals 1",
{
skip_on_cran()
expect_equal(
hcubature(
mf2_uv_full,
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6 changes: 6 additions & 0 deletions tests/testthat/test_dsmean.R
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Expand Up @@ -33,6 +33,7 @@ test_that("density of MLE sums up to one (normal distribution, one-armed) (exact

test_that("density of MLE sums up to one (t distribution, one-armed)",
{
skip_on_cran()
expect_equal(
dsmean(
Student(two_armed = FALSE),
Expand All @@ -50,6 +51,7 @@ test_that("density of MLE sums up to one (t distribution, one-armed)",

test_that("density of MLE sums up to one (t distribution, one-armed) (exact=TRUE)",
{
skip_on_cran()
expect_equal(
dsmean(
Student(two_armed = FALSE),
Expand All @@ -68,6 +70,7 @@ test_that("density of MLE sums up to one (t distribution, one-armed) (exact=TRUE

test_that("density of MLE sums up to one (normal distribution, two-armed, treatment group)",
{
skip_on_cran()
expect_equal(dsmeanT(Normal(),
designad,
.x <- seq(-2, 2, .h <- .01),
Expand All @@ -80,6 +83,7 @@ test_that("density of MLE sums up to one (normal distribution, two-armed, treatm

test_that("density of MLE sums up to one (normal distribution, two-armed, treatment group) (exact=TRUE)",
{
skip_on_cran()
expect_equal(dsmeanT(Normal(),
designad,
.x <- seq(-2, 2, .h <- .01),
Expand All @@ -92,6 +96,7 @@ test_that("density of MLE sums up to one (normal distribution, two-armed, treatm

test_that("density of MLE sums up to one (t distribution, two-armed, treatment group)",
{
skip_on_cran()
expect_equal(dsmeanT(Student(),
designad,
.x <- seq(-2, 2, .h <- .01),
Expand All @@ -104,6 +109,7 @@ test_that("density of MLE sums up to one (t distribution, two-armed, treatment g

test_that("density of MLE sums up to one (t distribution, two-armed, treatment group) (exact=TRUE)",
{
skip_on_cran()
expect_equal(dsmeanT(Student(),
designad,
.x <- seq(-2, 2, .h <- .1),
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1 change: 1 addition & 0 deletions tests/testthat/test_evaluate_estimator.R
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Expand Up @@ -103,6 +103,7 @@ test_that("TestAgreement of NaiveCI can be calculated",

test_that("TestAgreement of NaivePValue can be calculated",
{
skip_on_cran()
expect_lt(
evaluate_estimator(
score = TestAgreement(),
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3 changes: 3 additions & 0 deletions tests/testthat/test_integrals.R
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Expand Up @@ -39,6 +39,7 @@ test_that("integral over sample space is equal to 1 for case: unknown variance,
})
test_that("integral over sample space is equal to 1 for case: unknown variance, one-armed (exact=TRUE)",
{
skip_on_cran()
expect_equal(
int_uv(
design = designad,
Expand Down Expand Up @@ -89,6 +90,7 @@ test_that("integral over sample space is equal to 1 for case: unknown variance,
})
test_that("integral over sample space is equal to 1 for case: unknown variance, two-armed (exact=TRUE)",
{
skip_on_cran()
expect_equal(
int_uv(
design = designad,
Expand Down Expand Up @@ -136,6 +138,7 @@ test_that("integral over sample space is equal to 1 for case: unknown variance,
})
test_that("integral over sample space is equal to 1 for case: unknown variance, two-armed, full sampling distribution, exact n2",
{
skip_on_cran()
expect_equal(
int_uv_full(
design = designad,
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1 change: 1 addition & 0 deletions tests/testthat/test_pseudo_rao_blackwell.R
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@@ -1,5 +1,6 @@
test_that("Pseudo Rao-Blackwell estimator has less variance than Rao-Blackwell estimator",
{
skip_on_cran()
prb <- evaluate_estimator(score = Variance(),
estimator = PseudoRaoBlackwell(),
design = designad,
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