diff --git a/man/ocPredprob.Rd b/man/ocPredprob.Rd
index 63e17a09..25c8d9e2 100644
--- a/man/ocPredprob.Rd
+++ b/man/ocPredprob.Rd
@@ -117,124 +117,3 @@ The criteria for Decision 2 for Futility looks are :
 }
 }
 }
-\examples{
-# Here we illustrate an example for Decision 1 with the following assumptions :
-# True response rate or truep of the treatment group = 40\%
-# The following are the Final Stop rules respectively :
-# - Final look for Efficacy: Pr( response rate > 25\% ) > 60\% or P(response rate > p0) > tT
-# - Final look for Futility: Pr( response rate < 25\% ) < 60\% or P(response rate > p0) < tT
-# - Interim look for Efficacy: Pr( success at final ) > 80\% or P(success at final) > phiU
-# - Interim look for Futility: Pr( failure at final ) < 20\% or P(success at final) < phiL
-# We assume a prior of treatment arm parE = Beta(1,1), unless otherwise indicated.
-
-# Decision 1 with no wiggle.
-set.seed(20)
-result <- ocPredprob(
-  nnE = c(10, 20),
-  truep = 0.4,
-  p0 = 0.25,
-  tT = 0.6,
-  phiL = 0.2,
-  phiU = 0.8,
-  parE = c(1, 1),
-  sim = 50,
-  wiggle = FALSE,
-  decision1 = TRUE
-)
-result$oc
-
-# Decision 1 with wiggle.
-result <- ocPredprob(
-  nnE = c(10, 20),
-  truep = 0.4,
-  p0 = 0.25,
-  tT = 0.6,
-  phiL = 0.2,
-  phiU = 0.8,
-  parE = c(1, 1),
-  sim = 50,
-  wiggle = TRUE,
-  nnF = c(10, 20),
-  decision1 = TRUE
-)
-result$oc
-
-# Decision 1 with separate Futility and Efficacy looks at interim and final without wiggle.
-result <- ocPredprob(
-  nnE = c(10, 25, 30),
-  truep = 0.4,
-  p0 = 0.25,
-  p1 = 0.2,
-  tT = 0.6,
-  phiL = 0.2,
-  phiU = 0.8,
-  parE = c(1, 1),
-  sim = 50,
-  wiggle = FALSE,
-  nnF = c(10, 15, 20),
-  decision1 = TRUE
-)
-result$oc
-
-# Decision 1 with separate Futility and Efficacy looks at interim and final with wiggle.
-result <- ocPredprob(
-  nnE = c(10, 25, 30),
-  truep = 0.4,
-  p0 = 0.25,
-  p1 = 0.2,
-  tT = 0.6,
-  phiL = 0.2,
-  phiU = 0.8,
-  parE = c(1, 1),
-  sim = 50,
-  wiggle = TRUE,
-  nnF = c(10, 15, 20),
-  decision1 = TRUE
-)
-result$oc
-
-# Here we illustrate an example for Decision 2 with the following assumptions :
-# True response rate or truep of the treatment group = 60\%
-# The following are the Final Stop rules respectively :
-# - Final look for Efficacy: Pr( response rate > 25\% ) > 60\% or P(response rate > p0) > tT
-# - Final look for Futility: Pr( response rate < 25\% ) < 60\% or P(response rate < p1) > tF
-# - Interim look for Efficacy: Pr( success at final ) > 80\% or P(success at final) > phiU
-# - Interim look for Futility: Pr( failure at final ) > 80\% or P(failure at final) > phiFu
-# We assume a prior of treatment arm parE = Beta(1,1), unless otherwise indicated.
-
-# Decision 2 without wiggle.
-result <- ocPredprob(
-  nnE = c(10, 20),
-  truep = 0.6,
-  p0 = 0.25,
-  p1 = 0.25,
-  tT = 0.6,
-  tF = 0.6,
-  phiU = 0.8,
-  phiFu = 0.8,
-  parE = c(1, 1),
-  sim = 50,
-  wiggle = FALSE,
-  nnF = c(10, 20),
-  decision1 = FALSE
-)
-result$oc
-
-# Decision 2 with wiggle and with Futility only at final with non-uniform beta prior parE.
-result <- ocPredprob(
-  nnE = c(10, 25, 30),
-  truep = 0.6,
-  p0 = 0.25,
-  p1 = 0.25,
-  tT = 0.6,
-  tF = 0.6,
-  phiL = 0.8,
-  phiU = 0.8,
-  parE = c(11, 19),
-  sim = 50,
-  wiggle = TRUE,
-  nnF = 30,
-  decision1 = FALSE
-)
-result$oc
-}