diff --git a/R/dbetabinom.R b/R/dbetabinom.R
index a563510e..840631b0 100644
--- a/R/dbetabinom.R
+++ b/R/dbetabinom.R
@@ -83,9 +83,20 @@ h_getBetamixPost <- function(x, n, par, weights) {
   assert_number(x, lower = 0, upper = n, finite = TRUE)
   assert_number(n, lower = 0, finite = TRUE)
   assert_matrix(par, min.rows = 1, max.cols = 2, mode = "numeric")
-  assert_numeric(weights, min.len = 0, len = nrow(par), finite = TRUE)
-  # We renormalize weights.
-  weights <- weights / sum(weights)
+  assert_numeric(
+    weights,
+    min.len = 0,
+    len = nrow(par),
+    finite = TRUE
+  )
+  assert_true(all(weights >= 0))
+  # Correcting weights that do not sum to 1
+  if (sum(weights) != 1) {
+    warning("Weights have been corrected. Advise to review allocated weights")
+    # We renormalize weights.
+    weights <- weights / sum(weights)
+  }
+
   # We now compute updated parameters.
   postPar <- par
   postPar[, 1] <- postPar[, 1] + x
diff --git a/R/postprob.R b/R/postprob.R
index 383bf790..4f8ec9b3 100644
--- a/R/postprob.R
+++ b/R/postprob.R
@@ -68,7 +68,14 @@ postprobBeta <- function(x, n, p, a = 1, b = 1) {
 #'
 #' @example examples/postprob.R
 #' @export
-postprob <- function(x, n, p, parE = c(1, 1), weights, betamixPost, log.p = FALSE) {
+postprob <- function(
+    x,
+    n,
+    p,
+    parE = c(1, 1),
+    weights,
+    betamixPost,
+    log.p = FALSE) {
   if (missing(betamixPost)) {
     assert_flag(log.p)
     if (is.vector(parE)) {
@@ -79,7 +86,7 @@ postprob <- function(x, n, p, parE = c(1, 1), weights, betamixPost, log.p = FALS
     }
     assert_matrix(parE)
     if (missing(weights)) {
-      weights <- rep(1, nrow(parE))
+      weights <- rep(1 / nrow(parE), nrow(parE))
     }
     betamixPost <- lapply(
       x,
diff --git a/R/predprob.R b/R/predprob.R
index f550e018..59ce10b3 100644
--- a/R/predprob.R
+++ b/R/predprob.R
@@ -45,8 +45,7 @@
 #'
 #' @example examples/predprob.R
 #' @export
-predprob <- function(x, n, Nmax, p, thetaT, parE = c(1, 1),
-                     weights) {
+predprob <- function(x, n, Nmax, p, thetaT, parE = c(1, 1), weights) {
   # m = Nmax - n future observations
   m <- Nmax - n
   if (is.vector(parE)) {
@@ -55,18 +54,29 @@ predprob <- function(x, n, Nmax, p, thetaT, parE = c(1, 1),
     parE <- t(parE)
   }
   if (missing(weights)) {
-    weights <- rep(1, nrow(parE))
+    weights <- rep(1 / nrow(parE), nrow(parE))
   }
   betamixPost <- h_getBetamixPost(x = x, n = n, par = parE, weights = weights)
-
   density <- with(
     betamixPost,
     dbetabinomMix(x = 0:m, m = m, par = par, weights = weights)
   )
-  assert_numeric(density, lower = 0, upper = 1 + .Machine$double.eps, finite = TRUE, any.missing = FALSE)
+  assert_numeric(
+    density,
+    lower = 0,
+    upper = 1 + .Machine$double.eps,
+    finite = TRUE,
+    any.missing = FALSE
+  )
   assert_number(thetaT, lower = 0, upper = 1, finite = TRUE)
   # posterior probabilities to be above threshold p
-  posterior <- postprob(x = x + c(0:m), n = Nmax, p = p, parE = parE, weights = weights)
+  posterior <- postprob(
+    x = x + c(0:m),
+    n = Nmax,
+    p = p,
+    parE = parE,
+    weights = weights
+  )
   list(
     result = sum(density * (posterior > thetaT)),
     table = data.frame(
diff --git a/examples/postprob.R b/examples/postprob.R
index 5ca01017..46221f49 100644
--- a/examples/postprob.R
+++ b/examples/postprob.R
@@ -10,21 +10,23 @@ postprob(x = 16, n = 23, p = 0.60, par = c(0.6, 0.4))
 # 2 component beta mixture prior :
 # i.e., P_E ~ 0.6*beta(0.6,0.4) + 0.4*beta(1,1) and Pr(P_E > p | data) = 0.823
 postprob(
-  x = 16, n = 23, p = 0.60,
-  par =
-    rbind(
-      c(0.6, 0.4),
-      c(1, 1)
-    ),
+  x = 16,
+  n = 23,
+  p = 0.60,
+  par = rbind(
+    c(0.6, 0.4),
+    c(1, 1)
+  ),
   weights = c(0.6, 0.4)
 )
 
 postprob(
-  x = 0:23, n = 23, p = 0.60,
-  par =
-    rbind(
-      c(0.6, 0.4),
-      c(1, 1)
-    ),
+  x = 0:23,
+  n = 23,
+  p = 0.60,
+  par = rbind(
+    c(0.6, 0.4),
+    c(1, 1)
+  ),
   weights = c(0.6, 0.4)
 )
diff --git a/examples/predprob.R b/examples/predprob.R
index d3c98b8e..c80990ea 100644
--- a/examples/predprob.R
+++ b/examples/predprob.R
@@ -2,25 +2,41 @@
 # Nmax = 40, x = 16, n = 23, beta(0.6,0.4) prior distribution,
 # thetaT = 0.9. The control response rate is 60%:
 predprob(
-  x = 16, n = 23, Nmax = 40, p = 0.6, thetaT = 0.9,
+  x = 16,
+  n = 23,
+  Nmax = 40,
+  p = 0.6,
+  thetaT = 0.9,
   parE = c(0.6, 0.4)
 )
 
 # Lowering/Increasing the probability threshold thetaT of course increases
 # /decreases the predictive probability of success, respectively:
 predprob(
-  x = 16, n = 23, Nmax = 40, p = 0.6, thetaT = 0.8,
+  x = 16,
+  n = 23,
+  Nmax = 40,
+  p = 0.6,
+  thetaT = 0.8,
   parE = c(0.6, 0.4)
 )
 
 predprob(
-  x = 16, n = 23, Nmax = 40, p = 0.6, thetaT = 0.95,
+  x = 16,
+  n = 23,
+  Nmax = 40,
+  p = 0.6,
+  thetaT = 0.95,
   parE = c(0.6, 0.4)
 )
 
 # Mixed beta prior
 predprob(
-  x = 20, n = 23, Nmax = 40, p = 0.6, thetaT = 0.9,
+  x = 20,
+  n = 23,
+  Nmax = 40,
+  p = 0.6,
+  thetaT = 0.9,
   parE = rbind(c(1, 1), c(25, 15)),
-  weights = c(3, 1)
+  weights = c(0.5, 0.5)
 )
diff --git a/man/postprob.Rd b/man/postprob.Rd
index cf78cc9b..9e92d05b 100644
--- a/man/postprob.Rd
+++ b/man/postprob.Rd
@@ -53,22 +53,24 @@ postprob(x = 16, n = 23, p = 0.60, par = c(0.6, 0.4))
 # 2 component beta mixture prior :
 # i.e., P_E ~ 0.6*beta(0.6,0.4) + 0.4*beta(1,1) and Pr(P_E > p | data) = 0.823
 postprob(
-  x = 16, n = 23, p = 0.60,
-  par =
-    rbind(
-      c(0.6, 0.4),
-      c(1, 1)
-    ),
+  x = 16,
+  n = 23,
+  p = 0.60,
+  par = rbind(
+    c(0.6, 0.4),
+    c(1, 1)
+  ),
   weights = c(0.6, 0.4)
 )
 
 postprob(
-  x = 0:23, n = 23, p = 0.60,
-  par =
-    rbind(
-      c(0.6, 0.4),
-      c(1, 1)
-    ),
+  x = 0:23,
+  n = 23,
+  p = 0.60,
+  par = rbind(
+    c(0.6, 0.4),
+    c(1, 1)
+  ),
   weights = c(0.6, 0.4)
 )
 }
diff --git a/man/predprob.Rd b/man/predprob.Rd
index 27440d07..842d1e64 100644
--- a/man/predprob.Rd
+++ b/man/predprob.Rd
@@ -55,27 +55,43 @@ A table with the following contents will be included in the return output :
 # Nmax = 40, x = 16, n = 23, beta(0.6,0.4) prior distribution,
 # thetaT = 0.9. The control response rate is 60\%:
 predprob(
-  x = 16, n = 23, Nmax = 40, p = 0.6, thetaT = 0.9,
+  x = 16,
+  n = 23,
+  Nmax = 40,
+  p = 0.6,
+  thetaT = 0.9,
   parE = c(0.6, 0.4)
 )
 
 # Lowering/Increasing the probability threshold thetaT of course increases
 # /decreases the predictive probability of success, respectively:
 predprob(
-  x = 16, n = 23, Nmax = 40, p = 0.6, thetaT = 0.8,
+  x = 16,
+  n = 23,
+  Nmax = 40,
+  p = 0.6,
+  thetaT = 0.8,
   parE = c(0.6, 0.4)
 )
 
 predprob(
-  x = 16, n = 23, Nmax = 40, p = 0.6, thetaT = 0.95,
+  x = 16,
+  n = 23,
+  Nmax = 40,
+  p = 0.6,
+  thetaT = 0.95,
   parE = c(0.6, 0.4)
 )
 
 # Mixed beta prior
 predprob(
-  x = 20, n = 23, Nmax = 40, p = 0.6, thetaT = 0.9,
+  x = 20,
+  n = 23,
+  Nmax = 40,
+  p = 0.6,
+  thetaT = 0.9,
   parE = rbind(c(1, 1), c(25, 15)),
-  weights = c(3, 1)
+  weights = c(0.5, 0.5)
 )
 }
 \references{
diff --git a/tests/testthat/test-dbetabinom.R b/tests/testthat/test-dbetabinom.R
index e17a936e..60b3e547 100644
--- a/tests/testthat/test-dbetabinom.R
+++ b/tests/testthat/test-dbetabinom.R
@@ -170,7 +170,11 @@ test_that("dbetaMix gives the correct result with a 1 mixture component", {
 })
 
 test_that("dbetaMix gives the correct result with increased parameters", {
-  result <- dbetaMix(x = 0.3, par = rbind(c(0.2, 0.4), c(1, 2)), weights = c(0.1, 0.9))
+  result <- dbetaMix(
+    x = 0.3,
+    par = rbind(c(0.2, 0.4), c(1, 2)),
+    weights = c(0.1, 0.9)
+  )
   expect_equal(result, 1.307458, tolerance = 1e-4)
 })
 
@@ -180,48 +184,57 @@ test_that("dbetaMix gives error when weights do not sum to 1", {
       x = 0.3,
       par = rbind(c(0.2, 0.4), c(1, 1)),
       weights = c(1, 1)
-    ), "failed"
+    ),
+    "failed"
   )
 })
 
 test_that("dbetaMix gives the correct result as dbeta", {
   result <- dbetaMix(
-    x = 0.3, par = rbind(c(0.2, 0.4), c(1, 1)),
-    weights = c(0.6, 0.4)
-  )
-  result2 <- 0.6 * dbeta(
-    x = 0.3,
-    shape1 = 0.2,
-    shape2 = 0.4
-  ) + 0.4 * dbeta(
     x = 0.3,
-    shape1 = 1,
-    shape2 = 1,
+    par = rbind(c(0.2, 0.4), c(1, 1)),
+    weights = c(0.6, 0.4)
   )
+  result2 <- 0.6 *
+    dbeta(
+      x = 0.3,
+      shape1 = 0.2,
+      shape2 = 0.4
+    ) +
+    0.4 *
+      dbeta(
+        x = 0.3,
+        shape1 = 1,
+        shape2 = 1,
+      )
   expect_equal(result, result2, tolerance = 1e-4)
 })
 
 test_that("dbetaMix handles edge cases", {
   result_inf <- dbetaMix(
-    x = c(0, 1), par = rbind(c(0.2, 0.4), c(1, 1)),
+    x = c(0, 1),
+    par = rbind(c(0.2, 0.4), c(1, 1)),
     weights = c(0.6, 0.4)
   )
   expect_equal(result_inf, c(Inf, Inf))
 
   result_finite <- dbetaMix(
-    x = c(0, 1), par = rbind(c(2, 4), c(1, 1)),
+    x = c(0, 1),
+    par = rbind(c(2, 4), c(1, 1)),
     weights = c(0.6, 0.4)
   )
   expect_equal(result_finite, c(0.4, 0.4))
 
   result_right <- dbetaMix(
-    x = c(0, 1), par = rbind(c(0, 4), c(1, 1)),
+    x = c(0, 1),
+    par = rbind(c(0, 4), c(1, 1)),
     weights = c(0.6, 0.4)
   )
   expect_equal(result_right, c(Inf, 0.4))
 
   result_right <- dbetaMix(
-    x = c(NA, 1), par = rbind(c(0, 4), c(1, 1)),
+    x = c(NA, 1),
+    par = rbind(c(0, 4), c(1, 1)),
     weights = c(0.6, 0.4)
   )
   expect_equal(result_right, c(NA, 0.4))
@@ -244,11 +257,14 @@ test_that("h_getBetamixPost gives the correct beta-mixture parameters", {
 })
 
 test_that("h_getBetamixPost gives weight of 1 for a single beta distribution", {
-  results <- h_getBetamixPost(
-    x = 16,
-    n = 23,
-    par = rbind(c(1, 2)),
-    weights = 0.1
+  expect_warning(
+    results <- h_getBetamixPost(
+      x = 16,
+      n = 23,
+      par = rbind(c(1, 2)),
+      weights = 0.1
+    ),
+    "Weights have been corrected"
   )
   expected <- list(
     par = rbind(c(17, 9)),
@@ -269,13 +285,20 @@ test_that("h_getBetamixPost gives correct weights with 2 beta-mixture component"
 })
 
 test_that("h_getBetamixPost gives the correct weights when sum of weights is not 1 in beta-mixture", {
-  result <- h_getBetamixPost(
-    x = 16,
-    n = 23,
-    par = rbind(c(1, 2), c(3, 4), c(10, 10)),
-    weights = c(0.6, 0.4, 0.5)
+  expect_warning(
+    result <- h_getBetamixPost(
+      x = 16,
+      n = 23,
+      par = rbind(c(1, 2), c(3, 4), c(10, 10)),
+      weights = c(0.6, 0.4, 0.5)
+    ),
+    "Weights have been corrected"
+  )
+  expect_equal(
+    result$weights,
+    c(.2776991, 0.2683337, 0.4539671),
+    tolerance = 1e-4
   )
-  expect_equal(result$weights, c(.2776991, 0.2683337, 0.4539671), tolerance = 1e-4)
   expect_identical(result$par, rbind(c(17, 9), c(19, 11), c(26, 17)))
 })
 
@@ -286,6 +309,7 @@ test_that("h_getBetamixPost gives error when K rows of weights exceed length of
       n = 23,
       par = rbind(c(1, 2)),
       weights = c(0.6, 0.4)
-    ), "Must have length 1, but has length 2."
+    ),
+    "Must have length 1, but has length 2."
   )
 })
diff --git a/tests/testthat/test-postprob.R b/tests/testthat/test-postprob.R
index 7990db9b..74bac6cc 100644
--- a/tests/testthat/test-postprob.R
+++ b/tests/testthat/test-postprob.R
@@ -57,14 +57,42 @@ test_that("postprob gives incrementally higher values with increased x", {
 test_that("postprob works with vector x", {
   result <- postprob(x = 0:23, n = 23, p = 0.60, par = c(0.6, 0.4))
   expected <- c(
-    1.12066620085448e-10, 6.73786529927603e-09, 1.45879637562279e-07,
-    1.86374536434781e-06, 1.64656040420248e-05, 0.000108838231763851,
-    0.000564103325535708, 0.00236446983272442, 0.00819197194809839,
-    0.0238449136766029, 0.0590640325657381, 0.125847456119664,
-    0.232931221473374, 0.378259188739121, 0.54495891589689,
-    0.705949748288983, 0.835980805221058, 0.922929283049132,
-    0.970355725500809, 0.991009176245894, 0.997963909660055,
-    0.999685712592687, 0.999972679748126, 0.99999934483779
+    1.12066620085448e-10,
+    6.73786529927603e-09,
+    1.45879637562279e-07,
+    1.86374536434781e-06,
+    1.64656040420248e-05,
+    0.000108838231763851,
+    0.000564103325535708,
+    0.00236446983272442,
+    0.00819197194809839,
+    0.0238449136766029,
+    0.0590640325657381,
+    0.125847456119664,
+    0.232931221473374,
+    0.378259188739121,
+    0.54495891589689,
+    0.705949748288983,
+    0.835980805221058,
+    0.922929283049132,
+    0.970355725500809,
+    0.991009176245894,
+    0.997963909660055,
+    0.999685712592687,
+    0.999972679748126,
+    0.99999934483779
   )
   expect_equal(result, expected, tolerance = 1e-5)
 })
+
+test_that("postprob from beta mixture priors utilise updated weights", {
+  result <- postprob(x = 16, n = 23, p = 0.60, parE = c(2, 4), weights = 1)
+  expected <- postprob(
+    x = 16,
+    n = 23,
+    p = 0.60,
+    par = rbind(c(0.6, 0.4), c(2, 4)),
+    weights = c(0, 1)
+  )
+  expect_equal(result, expected, tolerance = 1e-7)
+})
diff --git a/tests/testthat/test-predprob.R b/tests/testthat/test-predprob.R
index 413ba6ba..6137a9dd 100644
--- a/tests/testthat/test-predprob.R
+++ b/tests/testthat/test-predprob.R
@@ -20,21 +20,28 @@ test_that("Higher thetaT decreases predprob", {
     parE = c(0.6, 0.4)
   )
   is_higher <- predprob(
-    x = 16, n = 23, Nmax = 40, p = 0.6, thetaT = 0.8,
+    x = 16,
+    n = 23,
+    Nmax = 40,
+    p = 0.6,
+    thetaT = 0.8,
     parE = c(0.6, 0.4)
   )
   expect_true(is_lower$result < is_higher$result)
 })
 
 test_that("predprob gives an error when x is a numeric", {
-  expect_error(predprob(
-    x = 16:20,
-    n = 23,
-    Nmax = 40,
-    p = 0.6,
-    thetaT = 0.9,
-    parE = c(0.6, 0.4)
-  ), "Must have length 1")
+  expect_error(
+    predprob(
+      x = 16:20,
+      n = 23,
+      Nmax = 40,
+      p = 0.6,
+      thetaT = 0.9,
+      parE = c(0.6, 0.4)
+    ),
+    "Must have length 1"
+  )
 })
 
 test_that("predprob gives an error when K columns of weights exceed rows parE", {
@@ -61,7 +68,8 @@ test_that("predprob gives an error when K columns of weights is less than rows p
       Nmax = 40,
       p = 0.6,
       thetaT = 0.9,
-      parE = rbind(c(0.6, 0.4), c(0.5, 0.5)), weights = 1
+      parE = rbind(c(0.6, 0.4), c(0.5, 0.5)),
+      weights = 1
     ),
     "Assertion on 'weights' failed: Must have length 2",
     fixed = TRUE
@@ -69,14 +77,17 @@ test_that("predprob gives an error when K columns of weights is less than rows p
 })
 
 test_that("predprob gives an error when thetaT exceeds 1", {
-  expect_error(predprob(
-    x = 16,
-    n = 23,
-    Nmax = 40,
-    p = 0.6,
-    thetaT = 2,
-    parE = c(0.6, 0.4)
-  ), "failed")
+  expect_error(
+    predprob(
+      x = 16,
+      n = 23,
+      Nmax = 40,
+      p = 0.6,
+      thetaT = 2,
+      parE = c(0.6, 0.4)
+    ),
+    "failed"
+  )
 })
 
 test_that("predprob gives the correct numeric result with a beta-mixture", {
@@ -87,69 +98,65 @@ test_that("predprob gives the correct numeric result with a beta-mixture", {
     p = 0.6,
     thetaT = 0.9,
     parE = rbind(c(1, 1), c(25, 15)),
-    weights = c(3, 1)
+    weights = c(0.6, 0.4)
   )
-  expect_equal(result$result, 0.9874431, tolerance = 1e-6)
+  expect_equal(result$result, 0.9831967, tolerance = 1e-6)
 })
 
 test_that("predprob gives an error when x exceeds interim n", {
-  expect_error(predprob(
-    x = 24,
-    n = 23,
-    Nmax = 40,
-    p = 0.6,
-    thetaT = 0.9,
-    parE = rbind(c(1, 1), c(25, 15)),
-    weights = c(3, 1)
-  ), "failed")
+  expect_error(
+    predprob(
+      x = 24,
+      n = 23,
+      Nmax = 40,
+      p = 0.6,
+      thetaT = 0.9,
+      parE = rbind(c(1, 1), c(25, 15)),
+      weights = c(3, 1)
+    ),
+    "failed"
+  )
 })
 
-test_that("predprob gives an error when Nmax is less than n", {
-  expect_error(predprob(
-    x = 16,
-    n = 23,
-    Nmax = 22,
-    p = 0.6,
-    thetaT = 0.9,
-    parE = rbind(c(1, 1), c(25, 15)),
-    weights = c(3, 1)
-  ), "failed")
+test_that("Warning length equal to length of x", {
+  captured_warnings <- capture_warnings({
+    result <- predprob(
+      x = 16,
+      n = 20,
+      Nmax = 22,
+      p = 0.6,
+      thetaT = 0.9,
+      parE = rbind(c(1, 1), c(25, 15)),
+      weights = c(3, 1)
+    )
+  })
+  expected <- data.frame(
+    counts = 0:2,
+    cumul_counts = c(20, 21, 22),
+    density = c(0.0738, 0.3651, 0.5611),
+    posterior = c(0.862329474749815, 0.928990451842824, 0.969938389163636),
+    success = c(FALSE, TRUE, TRUE)
+  )
+  expect_equal(
+    length(captured_warnings),
+    4,
+    info = "Should have generated one warning for each element in 'x' in the loop."
+  )
+  expect_equal(result$result, 0.9262315, tolerance = 1e-4)
+  expect_equal(result$table, expected, tolerance = 1e-4)
 })
 
-test_that("predprob gives correct list", {
-  result <- predprob(
-    x = 20,
-    n = 23,
-    Nmax = 40,
-    p = 0.6,
-    thetaT = 0.9,
-    parE = rbind(c(1, 1), c(25, 15)),
-    weights = c(3, 1)
-  )
-  expected <- list(
-    result = 0.987443066689065,
-    table = data.frame(
-      counts = 0:17,
-      cumul_counts = c(
-        23, 24, 25, 26, 27, 28, 29, 30, 31, 32,
-        33, 34, 35, 36, 37, 38, 39, 40
-      ),
-      density = c(
-        0, 0, 0, 0,
-        1e-04, 3e-04, 0.0011, 0.0031, 0.008, 0.0177, 0.0348, 0.0613,
-        0.0973, 0.1394, 0.1783, 0.1964, 0.1708, 0.0913
-      ),
-      posterior = c(
-        0.156,
-        0.2352, 0.3303, 0.4359, 0.5449, 0.65, 0.7447, 0.8244, 0.8871,
-        0.9327, 0.9634, 0.9821, 0.9923, 0.9972, 0.9991, 0.9998, 1,
-        1
-      ),
-      success = c(
-        FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
-        TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE
-      )
-    )
+test_that("predprob gives an error when Nmax is less than n", {
+  expect_error(
+    predprob(
+      x = 16,
+      n = 23,
+      Nmax = 22,
+      p = 0.6,
+      thetaT = 0.9,
+      parE = rbind(c(1, 1), c(25, 15)),
+      weights = c(0.6, 0.4)
+    ),
+    "failed"
   )
-  expect_identical(result, expected, tolerance = 1e-4)
 })