diff --git a/tests/testthat/test-auditPrior.R b/tests/testthat/test-auditPrior.R
index a86e21f2d..44eb2423d 100644
--- a/tests/testthat/test-auditPrior.R
+++ b/tests/testthat/test-auditPrior.R
@@ -46,6 +46,7 @@ test_that(desc = "(id: f2-v0.1.0-t2) Test for method = 'impartial'", {
 })
 
 test_that(desc = "(id: f2-v0.1.0-t3) Test for method = 'hyp'", {
+  testthat::skip_on_cran()
   prior <- auditPrior(materiality = 0.05, conf.level = 0.95, method = "hyp", likelihood = "binomial", p.hmin = 0.3)
   expect_equal(prior[["description"]]$alpha, 1)
   expect_equal(prior[["description"]]$beta, 6.954, tolerance = 0.001)
@@ -60,6 +61,7 @@ test_that(desc = "(id: f2-v0.1.0-t3) Test for method = 'hyp'", {
 })
 
 test_that(desc = "(id: f2-v0.1.0-t4) Test for method = 'arm'", {
+  testthat::skip_on_cran()
   prior <- auditPrior(materiality = 0.05, conf.level = 0.95, method = "arm", likelihood = "binomial", ir = 0.6, cr = 0.6)
   expect_equal(prior[["description"]]$alpha, 1)
   expect_equal(prior[["description"]]$beta, 20, tolerance = 0.001)
@@ -74,6 +76,7 @@ test_that(desc = "(id: f2-v0.1.0-t4) Test for method = 'arm'", {
 })
 
 test_that(desc = "(id: f2-v0.1.0-t5) Test for method = 'sample'", {
+  testthat::skip_on_cran()
   prior <- auditPrior(materiality = 0.05, conf.level = 0.95, method = "sample", likelihood = "binomial", n = 30, x = 1)
   expect_equal(prior[["description"]]$alpha, 2)
   expect_equal(prior[["description"]]$beta, 29)
@@ -88,6 +91,7 @@ test_that(desc = "(id: f2-v0.1.0-t5) Test for method = 'sample'", {
 })
 
 test_that(desc = "(id: f2-v0.1.0-t6) Test for method = 'factor'", {
+  testthat::skip_on_cran()
   prior <- auditPrior(materiality = 0.05, conf.level = 0.95, method = "factor", likelihood = "binomial", n = 30, x = 1, factor = 0.6)
   expect_equal(prior[["description"]]$alpha, 1.6, tolerance = 0.001)
   expect_equal(prior[["description"]]$beta, 17.4, tolerance = 0.001)
@@ -127,6 +131,7 @@ test_that(desc = "(id: f2-v0.4.0-t1) Test for method = 'impartial' with expected
 # jfa version 0.5.0
 
 test_that(desc = "(id: f2-v0.5.0-t1) Test for summary and print function", {
+  testthat::skip_on_cran()
   prior <- auditPrior(conf.level = 0.95, likelihood = "binomial", method = "default")
   invisible(capture.output(print(prior)))
   invisible(capture.output(summary(prior)))
@@ -135,6 +140,7 @@ test_that(desc = "(id: f2-v0.5.0-t1) Test for summary and print function", {
 })
 
 test_that(desc = "(id: f2-v0.5.0-t2) Test for plot function", {
+  testthat::skip_on_cran()
   prior <- auditPrior(conf.level = 0.95, likelihood = "binomial", method = "default", materiality = 0.05)
   p <- plot(prior)
   expect_equal(is.null(prior), FALSE)
@@ -154,6 +160,7 @@ test_that(desc = "(id: f2-v0.5.0-t2) Test for plot function", {
 # jfa version 0.5.3
 
 test_that(desc = "(id: f2-v0.5.3-t1) Test for bram method binomial", {
+  testthat::skip_on_cran()
   N <- 20000
   materiality <- 2000
   expectedMisstatement <- 300
@@ -167,6 +174,7 @@ test_that(desc = "(id: f2-v0.5.3-t1) Test for bram method binomial", {
 })
 
 test_that(desc = "(id: f2-v0.5.3-t2) Test for bram method poisson", {
+  testthat::skip_on_cran()
   N <- 20000
   materiality <- 2000
   expectedMisstatement <- 300
@@ -185,18 +193,21 @@ test_that(desc = "(id: f2-v0.5.3-t2) Test for bram method poisson", {
 # jfa version 0.6.0
 
 test_that(desc = "(id: f2-v0.6.0-t1) Test for param method binomial", {
+  testthat::skip_on_cran()
   prior <- auditPrior(materiality = 0.05, likelihood = "binomial", method = "param", alpha = 5, beta = 10)
   expect_equal(prior[["description"]]$alpha, 5)
   expect_equal(prior[["description"]]$beta, 10)
 })
 
 test_that(desc = "(id: f2-v0.6.0-t2) Test for param method poisson", {
+  testthat::skip_on_cran()
   prior <- auditPrior(materiality = 0.05, likelihood = "poisson", method = "param", alpha = 5, beta = 10)
   expect_equal(prior[["description"]]$alpha, 5)
   expect_equal(prior[["description"]]$beta, 10)
 })
 
 test_that(desc = "(id: f2-v0.6.0-t1) Test for param method hypergeometric", {
+  testthat::skip_on_cran()
   prior <- auditPrior(materiality = 0.05, likelihood = "hypergeometric", method = "param", alpha = 5, beta = 10, N = 100)
   expect_equal(prior[["description"]]$alpha, 5)
   expect_equal(prior[["description"]]$beta, 10)
diff --git a/tests/testthat/test-digit-test.R b/tests/testthat/test-digit-test.R
index 47c1e8b3b..8b8885ffb 100644
--- a/tests/testthat/test-digit-test.R
+++ b/tests/testthat/test-digit-test.R
@@ -16,6 +16,7 @@
 context("Validation of function digit_test")
 
 test_that(desc = "Print and plot call", {
+  testthat::skip_on_cran()
   data("sinoForest")
   res <- digit_test(x = sinoForest$value, check = "first", reference = "benford")
   p <- plot(res)
@@ -32,6 +33,7 @@ test_that(desc = "Validate Derks et al. (2020)", {
 })
 
 test_that(desc = "Validate uniform distribution", {
+  testthat::skip_on_cran()
   res <- digit_test(x = 1:9, check = "first", reference = "uniform")
   expect_equal(as.numeric(res$n), 9)
   expect_equal(as.numeric(res$statistic), 0)
@@ -40,6 +42,7 @@ test_that(desc = "Validate uniform distribution", {
 })
 
 test_that(desc = "Validate benford.analysis package first digits", {
+  testthat::skip_on_cran()
   ba <- benford.analysis::benford(data = sinoForest$value, number.of.digits = 1)
   dt <- digit_test(x = sinoForest$value, check = "first")
   expect_equal(as.numeric(ba$bfd$data.dist.freq), as.numeric(dt$observed))
@@ -49,6 +52,7 @@ test_that(desc = "Validate benford.analysis package first digits", {
 })
 
 test_that(desc = "Validate benford.analysis package first and second digits", {
+  testthat::skip_on_cran()
   ba <- benford.analysis::benford(data = sinoForest$value, number.of.digits = 2)
   dt <- digit_test(x = sinoForest$value, check = "firsttwo")
   expect_equal(as.numeric(ba$bfd$data.dist.freq), as.numeric(dt$observed))
@@ -58,6 +62,7 @@ test_that(desc = "Validate benford.analysis package first and second digits", {
 })
 
 test_that(desc = "Validate BenfordTests package first digits", {
+  testthat::skip_on_cran()
   bt <- BenfordTests::chisq.benftest(x = sinoForest$value, digits = 1)
   dt <- digit_test(x = sinoForest$value, check = "first")
   expect_equal(as.numeric(bt$statistic), as.numeric(dt$statistic))
@@ -65,6 +70,7 @@ test_that(desc = "Validate BenfordTests package first digits", {
 })
 
 test_that(desc = "Validate BeyondBenford package first digits", {
+  testthat::skip_on_cran()
   bb <- BeyondBenford::chi2(sinoForest$value, mod = "ben", dig = 1, pval = 1)
   dt <- digit_test(x = sinoForest$value, check = "first")
   expect_equal(as.numeric(bb$chi2[2]), as.numeric(dt$statistic))
@@ -78,11 +84,13 @@ test_that(desc = "Validate Derks et al. (2020)", {
 })
 
 test_that(desc = "Validate uniform distribution", {
+  testthat::skip_on_cran()
   res <- digit_test(x = 1:9, check = "first", reference = "uniform", prior = TRUE)
   expect_equal(1 / as.numeric(res$bf), 22.77012458)
 })
 
 test_that(desc = "Validate benford.analysis package", {
+  testthat::skip_on_cran()
   ba <- benford.analysis::benford(data = sinoForest$value, number.of.digits = 1)
   dt <- digit_test(x = sinoForest$value, check = "first")
   expect_equal(as.numeric(ba$bfd$data.dist.freq), as.numeric(dt$observed))
diff --git a/tests/testthat/test-evaluation.R b/tests/testthat/test-evaluation.R
index c00d4ac7f..1b09b6d0e 100644
--- a/tests/testthat/test-evaluation.R
+++ b/tests/testthat/test-evaluation.R
@@ -89,6 +89,7 @@ test_that(desc = "(id: f3-v0.1.0-t7) Evaluation with stringer method", {
 })
 
 test_that(desc = "(id: f3-v0.1.0-t8) Evaluation with stringer.meikle method", {
+  testthat::skip_on_cran()
   set.seed(1)
   population <- data.frame(ID = sample(1000:100000, size = 1000, replace = FALSE), bookValue = runif(n = 1000, min = 100, max = 500))
   jfaRes <- planning(conf.level = 0.95, materiality = 0.05, likelihood = "poisson")
@@ -105,6 +106,7 @@ test_that(desc = "(id: f3-v0.1.0-t8) Evaluation with stringer.meikle method", {
 })
 
 test_that(desc = "(id: f3-v0.1.0-t9) Evaluation with stringer.lta method", {
+  testthat::skip_on_cran()
   set.seed(1)
   population <- data.frame(ID = sample(1000:100000, size = 1000, replace = FALSE), bookValue = runif(n = 1000, min = 100, max = 500))
   jfaRes <- planning(conf.level = 0.95, materiality = 0.05, likelihood = "poisson")
@@ -121,6 +123,7 @@ test_that(desc = "(id: f3-v0.1.0-t9) Evaluation with stringer.lta method", {
 })
 
 test_that(desc = "(id: f3-v0.1.0-t10) Evaluation with stringer.pvz method", {
+  testthat::skip_on_cran()
   set.seed(1)
   population <- data.frame(ID = sample(1000:100000, size = 1000, replace = FALSE), bookValue = runif(n = 1000, min = 100, max = 500))
   jfaRes <- planning(conf.level = 0.95, materiality = 0.05, likelihood = "poisson")
@@ -137,6 +140,7 @@ test_that(desc = "(id: f3-v0.1.0-t10) Evaluation with stringer.pvz method", {
 })
 
 test_that(desc = "(id: f3-v0.1.0-t11) Evaluation with rohrbach method", {
+  testthat::skip_on_cran()
   set.seed(1)
   population <- data.frame(ID = sample(1000:100000, size = 1000, replace = FALSE), bookValue = runif(n = 1000, min = 100, max = 500))
   jfaRes <- planning(conf.level = 0.95, materiality = 0.05, likelihood = "poisson")
@@ -147,6 +151,7 @@ test_that(desc = "(id: f3-v0.1.0-t11) Evaluation with rohrbach method", {
 })
 
 test_that(desc = "(id: f3-v0.1.0-t12) Evaluation with moment method", {
+  testthat::skip_on_cran()
   set.seed(1)
   population <- data.frame(ID = sample(1000:100000, size = 1000, replace = FALSE), bookValue = runif(n = 1000, min = 100, max = 500))
   jfaRes <- planning(conf.level = 0.95, materiality = 0.05, likelihood = "poisson")
@@ -160,6 +165,7 @@ test_that(desc = "(id: f3-v0.1.0-t12) Evaluation with moment method", {
 })
 
 test_that(desc = "(id: f3-v0.1.0-t13) Evaluation with direct method", {
+  testthat::skip_on_cran()
   data("BuildIt")
   BuildIt$inSample <- c(rep(1, 100), rep(0, 3400))
   BuildIt_sample <- subset(BuildIt, BuildIt$inSample == 1)
@@ -170,6 +176,7 @@ test_that(desc = "(id: f3-v0.1.0-t13) Evaluation with direct method", {
 })
 
 test_that(desc = "(id: f3-v0.1.0-t14) Evaluation with difference method", {
+  testthat::skip_on_cran()
   data("BuildIt")
   BuildIt$inSample <- c(rep(1, 100), rep(0, 3400))
   BuildIt_sample <- subset(BuildIt, BuildIt$inSample == 1)
@@ -180,6 +187,7 @@ test_that(desc = "(id: f3-v0.1.0-t14) Evaluation with difference method", {
 })
 
 test_that(desc = "(id: f3-v0.1.0-t15) Evaluation with quotient method", {
+  testthat::skip_on_cran()
   data("BuildIt")
   BuildIt$inSample <- c(rep(1, 100), rep(0, 3400))
   BuildIt_sample <- subset(BuildIt, BuildIt$inSample == 1)
@@ -200,6 +208,7 @@ test_that(desc = "(id: f3-v0.1.0-t16) Evaluation with regression method", {
 })
 
 test_that(desc = "(id: f3-v0.1.0-t17) Evaluation with Cox and Snell method", {
+  testthat::skip_on_cran()
   set.seed(1)
   population <- data.frame(ID = sample(1000:100000, size = 1000, replace = FALSE), bookValue = runif(n = 1000, min = 100, max = 500))
   jfaRes <- planning(conf.level = 0.95, materiality = 0.05, expected = 0.025)
@@ -216,6 +225,7 @@ test_that(desc = "(id: f3-v0.1.0-t17) Evaluation with Cox and Snell method", {
 # jfa version 0.3.0
 
 test_that(desc = "(id: f3-v0.3.0-t1) Evaluation with counts and stringer method", {
+  testthat::skip_on_cran()
   set.seed(1)
   population <- data.frame(ID = sample(1000:100000, size = 1000, replace = FALSE), bookValue = runif(n = 1000, min = 100, max = 500))
   jfaRes <- planning(conf.level = 0.95, materiality = 0.05, expected = 0.025)
@@ -250,6 +260,7 @@ test_that(desc = "(id: f3-v0.4.0-t1) Bayes factors", {
 # jfa version 0.5.0
 
 test_that(desc = "(id: f3-v0.5.0-t1) Test for mpu estimator", {
+  testthat::skip_on_cran()
   sample <- data.frame(ID = 1:100, ist = rnorm(mean = 1000, n = 100))
   sample$soll <- sample$ist
   sample$ist[1] <- 120
@@ -261,6 +272,7 @@ test_that(desc = "(id: f3-v0.5.0-t1) Test for mpu estimator", {
 })
 
 test_that(desc = "(id: f3-v0.5.0-t1) Test for frequentist summary and print function", {
+  testthat::skip_on_cran()
   set.seed(1)
   population <- data.frame(ID = sample(1000:100000, size = 1000, replace = FALSE), bookValue = runif(n = 1000, min = 100, max = 500))
   jfaRes <- planning(conf.level = 0.95, materiality = 0.05, likelihood = "poisson")
@@ -280,6 +292,7 @@ test_that(desc = "(id: f3-v0.5.0-t1) Test for frequentist summary and print func
 })
 
 test_that(desc = "(id: f3-v0.2.0-t2) Test for Bayesian summary function", {
+  testthat::skip_on_cran()
   set.seed(1)
   population <- data.frame(ID = sample(1000:100000, size = 1000, replace = FALSE), bookValue = runif(n = 1000, min = 100, max = 500))
   jfaRes <- planning(conf.level = 0.95, materiality = 0.05, likelihood = "poisson")
@@ -294,6 +307,7 @@ test_that(desc = "(id: f3-v0.2.0-t2) Test for Bayesian summary function", {
 })
 
 test_that(desc = "(id: f3-v0.2.0-t4) Test for Bayesian plot function", {
+  testthat::skip_on_cran()
   set.seed(1)
   population <- data.frame(ID = sample(1000:100000, size = 1000, replace = FALSE), bookValue = runif(n = 1000, min = 100, max = 500))
   samp <- selection(population, size = 100, units = "items", method = "random")$sample
@@ -367,6 +381,7 @@ test_that(desc = "(id: f3-v0.6.0-t2) Test Bayes factors for gamma prior", {
 })
 
 test_that(desc = "(id: f3-v0.6.0-t3) Test Bayes factors for beta-binomial prior", {
+  testthat::skip_on_cran()
   # Compute a Bayes factor from a noninformative beta-binomial prior
   BF <- evaluation(materiality = 0.03, n = 160, x = 1, prior = auditPrior(method = "default", likelihood = "hypergeometric", N.units = 1000))$posterior$hypotheses$bf.h1
   expect_equal(BF, 943.4715321)
@@ -540,6 +555,7 @@ test_that(desc = "(id: f3-v0.6.5-t6) Validate poststratification with stan examp
 })
 
 test_that(desc = "(id: f3-v0.6.5-t7) Test evaluation with non-conjugate priors", {
+  testthat::skip_on_cran()
   # Cannot test for consistency due to sampling differences on OS's
   prior <- auditPrior(method = "param", likelihood = "normal", alpha = 0.025, beta = 0.05)
   res <- evaluation(materiality = 0.03, x = 0, n = 53, prior = prior, method = "binomial")
diff --git a/tests/testthat/test-model-fairness.R b/tests/testthat/test-model-fairness.R
index 6e584de90..dc305530d 100644
--- a/tests/testthat/test-model-fairness.R
+++ b/tests/testthat/test-model-fairness.R
@@ -16,6 +16,7 @@
 context("Validation of function model_fairness")
 
 test_that(desc = "Benchmark against fairness package", {
+  testthat::skip_on_cran()
   data("compas")
   # Demographic parity
   jfa_dp <- model_fairness(compas, "Ethnicity", "TwoYrRecidivism", "Predicted", privileged = "Caucasian", positive = "yes", metric = "dp")
diff --git a/tests/testthat/test-planning.R b/tests/testthat/test-planning.R
index f2d10c1e1..4318fef96 100644
--- a/tests/testthat/test-planning.R
+++ b/tests/testthat/test-planning.R
@@ -24,18 +24,21 @@ test_that(desc = "(id: f5-v0.1.0-t1) Frequentist Poisson 1% materiality", {
 })
 
 test_that(desc = "(id: f5-v0.1.0-t2) Frequentist Poisson 5% materiality", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0, likelihood = "poisson")
   expect_equal(jfaRes[["n"]], 60)
   expect_equal(jfaRes[["x"]], 0)
 })
 
 test_that(desc = "(id: f5-v0.1.0-t3) Frequentist Poisson 5% materiality 2.5% errors", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0.025, likelihood = "poisson")
   expect_equal(jfaRes[["n"]], 231)
   expect_equal(jfaRes[["x"]], 5.78, tolerance = 0.001)
 })
 
 test_that(desc = "(id: f5-v0.1.0-t4) Frequentist Poisson 5% materiality 2% errors", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 2, likelihood = "poisson")
   expect_equal(jfaRes[["n"]], 126)
   expect_equal(jfaRes[["x"]], 2)
@@ -48,30 +51,35 @@ test_that(desc = "(id: f5-v0.1.0-t5) Bayesian Poisson 5% materiality 2.5% errors
 })
 
 test_that(desc = "(id: f5-v0.1.0-t7) Frequentist binomial 1% materiality", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.01, conf.level = 0.95, expected = 0, likelihood = "binomial")
   expect_equal(jfaRes[["n"]], 299)
   expect_equal(jfaRes[["x"]], 0)
 })
 
 test_that(desc = "(id: f5-v0.1.0-t8) Frequentist binomial 5% materiality", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0, likelihood = "binomial")
   expect_equal(jfaRes[["n"]], 59)
   expect_equal(jfaRes[["x"]], 0)
 })
 
 test_that(desc = "(id: f5-v0.1.0-t9) Frequentist binomial 5% materiality 2.5% errors", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0.025, likelihood = "binomial")
   expect_equal(jfaRes[["n"]], 234)
   expect_equal(jfaRes[["x"]], 6, tolerance = 0.001)
 })
 
 test_that(desc = "(id: f5-v0.1.0-t10) Frequentist binomial 5% materiality 2 errors", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 2, likelihood = "binomial")
   expect_equal(jfaRes[["n"]], 124)
   expect_equal(jfaRes[["x"]], 2)
 })
 
 test_that(desc = "(id: f5-v0.1.0-t11) Bayesian binomial 5% materiality 2.5% errors", {
+  testthat::skip_on_cran()
   prior <- auditPrior(method = "default", likelihood = "binomial")
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0.025, likelihood = "binomial", prior = prior)
   expect_equal(jfaRes[["n"]], 220)
@@ -79,30 +87,35 @@ test_that(desc = "(id: f5-v0.1.0-t11) Bayesian binomial 5% materiality 2.5% erro
 })
 
 test_that(desc = "(id: f5-v0.1.0-t13) Frequentist hypergeometric 1% materiality", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.01, conf.level = 0.95, expected = 0, likelihood = "hypergeometric", N.units = 1000)
   expect_equal(jfaRes[["n"]], 258)
   expect_equal(jfaRes[["x"]], 0)
 })
 
 test_that(desc = "(id: f5-v0.1.0-t14) Frequentist hypergeometric 5% materiality", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0, likelihood = "hypergeometric", N.units = 1000)
   expect_equal(jfaRes[["n"]], 57)
   expect_equal(jfaRes[["x"]], 0)
 })
 
 test_that(desc = "(id: f5-v0.1.0-t15) Frequentist hypergeometric 5% materiality 2.5% errors", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0.025, likelihood = "hypergeometric", N.units = 1000)
   expect_equal(jfaRes[["n"]], 197)
   expect_equal(jfaRes[["x"]], 5)
 })
 
 test_that(desc = "(id: f5-v0.1.0-t16) Frequentist hypergeometric 5% materiality 2 errors", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 2, likelihood = "hypergeometric", N.units = 1000)
   expect_equal(jfaRes[["n"]], 119)
   expect_equal(jfaRes[["x"]], 2)
 })
 
 test_that(desc = "(id: f5-v0.1.0-t17) Bayesian hypergeometric 5% materiality 2.5% errors", {
+  testthat::skip_on_cran()
   prior <- auditPrior(method = "default", likelihood = "hypergeometric", N.units = 1000)
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0.025, likelihood = "hypergeometric", N.units = 1000, prior = prior)
   expect_equal(jfaRes[["n"]], 196)
@@ -110,6 +123,7 @@ test_that(desc = "(id: f5-v0.1.0-t17) Bayesian hypergeometric 5% materiality 2.5
 })
 
 test_that(desc = "(id: f5-v0.1.0-t19) Bayesian binomial 2% precision 5% materiality 2.5% errors impartial prior", {
+  testthat::skip_on_cran()
   jfaPrior <- auditPrior(materiality = 0.05, conf.level = 0.95, method = "impartial", expected = 0.025, likelihood = "binomial")
   jfaRes <- planning(materiality = 0.05, min.precision = 0.02, conf.level = 0.95, expected = 0.025, likelihood = "binomial", N.units = 1000, prior = jfaPrior)
   expect_equal(jfaRes[["n"]], 284)
@@ -117,6 +131,7 @@ test_that(desc = "(id: f5-v0.1.0-t19) Bayesian binomial 2% precision 5% material
 })
 
 test_that(desc = "(id: f5-v0.1.0-t20) Bayesian binomial 5% materiality 1% errors hypotheses prior", {
+  testthat::skip_on_cran()
   jfaPrior <- auditPrior(materiality = 0.05, conf.level = 0.95, method = "hyp", p.hmin = 0.7, likelihood = "binomial")
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0.01, likelihood = "binomial", N.units = 1000, prior = jfaPrior)
   expect_equal(jfaRes[["n"]], 55)
@@ -124,6 +139,7 @@ test_that(desc = "(id: f5-v0.1.0-t20) Bayesian binomial 5% materiality 1% errors
 })
 
 test_that(desc = "(id: f5-v0.1.0-t21) Bayesian poisson 5% materiality 1% errors factor prior", {
+  testthat::skip_on_cran()
   jfaPrior <- auditPrior(materiality = 0.05, conf.level = 0.95, method = "factor", factor = 0.6, n = 58, x = 0, expected = 0.025, likelihood = "binomial")
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0.01, likelihood = "binomial", N.units = 1000, prior = jfaPrior)
   expect_equal(jfaRes[["n"]], 38)
@@ -131,6 +147,7 @@ test_that(desc = "(id: f5-v0.1.0-t21) Bayesian poisson 5% materiality 1% errors
 })
 
 test_that(desc = "(id: f5-v0.1.0-t22) Bayesian poisson 3% materiality 1.3% errors sample prior", {
+  testthat::skip_on_cran()
   jfaPrior <- auditPrior(materiality = 0.03, conf.level = 0.95, method = "sample", n = 58, x = 0, expected = 0.025, likelihood = "binomial")
   jfaRes <- planning(materiality = 0.03, conf.level = 0.95, expected = 0.013, likelihood = "binomial", N.units = 1000, prior = jfaPrior)
   expect_equal(jfaRes[["n"]], 143)
@@ -138,6 +155,7 @@ test_that(desc = "(id: f5-v0.1.0-t22) Bayesian poisson 3% materiality 1.3% error
 })
 
 test_that(desc = "(id: f5-v0.1.0-t23) Frequentist poisson 3% materiality 1.3% errors 5% min precision", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.03, conf.level = 0.95, expected = 0.013, min.precision = 0.05, likelihood = "binomial", N.units = 1000)
   expect_equal(jfaRes[["n"]], 303)
   expect_equal(jfaRes[["x"]], 4, tolerance = 0.001)
@@ -146,6 +164,7 @@ test_that(desc = "(id: f5-v0.1.0-t23) Frequentist poisson 3% materiality 1.3% er
 # jfa version 0.2.0
 
 test_that(desc = "(id: f5-v0.2.0-t1) Bayesian poisson 3% materiality 1.3% errors 5% min precision standard prior", {
+  testthat::skip_on_cran()
   prior <- auditPrior(method = "default", likelihood = "binomial")
   jfaRes <- planning(materiality = 0.03, conf.level = 0.95, expected = 0.013, min.precision = 0.05, likelihood = "binomial", N.units = 1000, prior = prior)
   expect_equal(jfaRes[["n"]], 293)
@@ -153,12 +172,14 @@ test_that(desc = "(id: f5-v0.2.0-t1) Bayesian poisson 3% materiality 1.3% errors
 })
 
 test_that(desc = "(id: f5-v0.2.0-t2) Bayesian poisson 100% materiality 0% errors 2% min precision standard prior", {
+  testthat::skip_on_cran()
   jfaRes <- planning(conf.level = 0.95, min.precision = 0.02, likelihood = "poisson", prior = TRUE)
   expect_equal(jfaRes[["n"]], 149)
   expect_equal(jfaRes[["x"]], 0)
 })
 
 test_that(desc = "(id: f5-v0.2.0-t3) Bayesian poisson 100% materiality 1% errors 2% min precision standard prior", {
+  testthat::skip_on_cran()
   jfaRes <- planning(conf.level = 0.95, min.precision = 0.02, expected = 0.01, likelihood = "poisson", prior = TRUE)
   expect_equal(jfaRes[["n"]], 219)
   expect_equal(jfaRes[["x"]], 2.19, tolerance = 0.001)
@@ -170,6 +191,7 @@ test_that(desc = "(id: f5-v0.2.0-t3) Bayesian poisson 100% materiality 1% errors
 # jfa version 0.4.0
 
 test_that(desc = "(id: f5-v0.4.0-t1) Expected Bayes factors for zero expected errors", {
+  testthat::skip_on_cran()
   prior <- auditPrior(method = "strict", likelihood = "poisson")
   jfaRes <- planning(conf.level = 0.95, materiality = 0.02, expected = 0, likelihood = "poisson", prior = prior)
   expect_equal(jfaRes[["posterior"]][["hypotheses"]]$odds.h1, 19.08554, tolerance = 0.001)
@@ -184,6 +206,7 @@ test_that(desc = "(id: f5-v0.4.0-t1) Expected Bayes factors for zero expected er
 })
 
 test_that(desc = "(id: f5-v0.4.0-t2) Expected Bayes factors for expected errors > 0", {
+  testthat::skip_on_cran()
   prior <- auditPrior(method = "strict", likelihood = "poisson")
   jfaRes <- planning(conf.level = 0.95, materiality = 0.02, expected = 0.01, likelihood = "poisson", prior = prior)
   expect_equal(jfaRes[["posterior"]][["hypotheses"]]$odds.h1, 19.01191777, tolerance = 0.001)
@@ -198,6 +221,7 @@ test_that(desc = "(id: f5-v0.4.0-t2) Expected Bayes factors for expected errors
 })
 
 test_that(desc = "(id: f5-v0.4.0-t3) Expected Bayes factors for impartial priors", {
+  testthat::skip_on_cran()
   prior <- auditPrior(materiality = 0.02, conf.level = 0.95, method = "impartial", likelihood = "poisson")
   jfaRes <- planning(conf.level = 0.95, materiality = 0.02, prior = prior)
   expect_equal(jfaRes[["posterior"]][["hypotheses"]]$bf.h1, 19.35135, tolerance = 0.001)
@@ -210,6 +234,7 @@ test_that(desc = "(id: f5-v0.4.0-t3) Expected Bayes factors for impartial priors
 # jfa version 0.5.0
 
 test_that(desc = "(id: f5-v0.5.0-t1) Test for frequentist summary and print function", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.01, conf.level = 0.95, expected = 0, likelihood = "poisson")
   invisible(capture.output(print(jfaRes)))
   invisible(capture.output(summary(jfaRes)))
@@ -218,6 +243,7 @@ test_that(desc = "(id: f5-v0.5.0-t1) Test for frequentist summary and print func
 })
 
 test_that(desc = "(id: f5-v0.5.0-t2) Test for Bayesian summary and print function", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.01, conf.level = 0.95, expected = 0, likelihood = "poisson", prior = TRUE)
   invisible(capture.output(print(jfaRes)))
   invisible(capture.output(summary(jfaRes)))
@@ -228,6 +254,7 @@ test_that(desc = "(id: f5-v0.5.0-t2) Test for Bayesian summary and print functio
 })
 
 test_that(desc = "(id: f5-v0.5.0-t4) Test for Bayesian plot function", {
+  testthat::skip_on_cran()
   jfaRes <- planning(min.precision = 0.02, conf.level = 0.95, expected = 0, likelihood = "poisson", prior = TRUE)
   p <- plot(jfaRes)
   expect_equal(is.null(p), FALSE)
@@ -259,6 +286,7 @@ test_that(desc = "(id: f5-v0.5.0-t4) Test for Bayesian plot function", {
 # jfa version 0.5.2
 
 test_that(desc = "(id: f5-v0.5.2-t1) Test for change in Hypergeometric mode calculation", {
+  testthat::skip_on_cran()
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0, likelihood = "hypergeometric", N.units = 10000)
   modeDist <- ceiling((jfaRes[["ub"]] - jfaRes[["precision"]]) * 10000)
   expect_equal(jfaRes[["n"]], 59)
@@ -266,6 +294,7 @@ test_that(desc = "(id: f5-v0.5.2-t1) Test for change in Hypergeometric mode calc
 })
 
 test_that(desc = "(id: f5-v0.5.2-t2) Test for change in beta-binomial mode calculation", {
+  testthat::skip_on_cran()
   prior <- auditPrior(method = "default", likelihood = "hypergeometric", N.units = 10000)
   jfaRes <- planning(materiality = 0.05, conf.level = 0.95, expected = 0, likelihood = "hypergeometric", N = 10000, prior = prior)
   modeDist <- ceiling((jfaRes[["ub"]] - jfaRes[["precision"]]) * 10000)
@@ -279,6 +308,7 @@ test_that(desc = "(id: f5-v0.5.2-t2) Test for change in beta-binomial mode calcu
 # jfa version 0.6.5
 
 test_that(desc = "(id: f5-v0.6.5-t1) Test Bayesian planning with different uniform priors, 5% materiality", {
+  testthat::skip_on_cran()
   set.seed(1)
   prior1 <- auditPrior(method = "default", likelihood = "binomial")
   prior2 <- auditPrior(method = "param", likelihood = "uniform", alpha = 0, beta = 1)
diff --git a/tests/testthat/test-repeated-values.R b/tests/testthat/test-repeated-values.R
index 9eb2e8c8e..ed4282a68 100644
--- a/tests/testthat/test-repeated-values.R
+++ b/tests/testthat/test-repeated-values.R
@@ -16,6 +16,7 @@
 context("Validation of function repeated_test")
 
 test_that(desc = "Print and plot call", {
+  testthat::skip_on_cran()
   data("sanitizer")
   res <- repeated_test(x = sanitizer$value, check = "last", method = "af", samples = 1) # Adjusted from 500 to 1 for check time control
   p <- plot(res)
@@ -23,6 +24,7 @@ test_that(desc = "Print and plot call", {
 })
 
 test_that(desc = "Validate Datacolada[77]", {
+  testthat::skip_on_cran()
   data("sanitizer")
   res <- repeated_test(x = sanitizer$value, check = "last", method = "af", samples = 1) # Adjusted from 500 to 1 for check time control
   expect_equal(as.numeric(res$statistic), 1.5225)