#\examples<>

#<ss.cons.2binom.avg.hpdlimits>
accepted.pdiff <- 0.01
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.avg.hpdlimits(accepted.pdiff, prior1, prior2)

#<ss.cons.2binom.avg.hpdlimits.mymarg>
accepted.pdiff <- 0.01
clinical.prior <- list(alpha=c(100, 100), beta=c(25, 40))
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.avg.hpdlimits.mymarg(accepted.pdiff, prior1, prior2, clinical.prior)

#<ss.cons.2binom.avg.hpdlimits.bothmarg>
accepted.pdiff <- 0.01
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.avg.hpdlimits.bothmarg(accepted.pdiff, prior1, prior2)

#<ss.cons.2binom.prob.hpdlimits.bothmarg>
accepted.pdiff <- 0.01
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.prob.hpdlimits.bothmarg(accepted.pdiff, prior1, prior2, prob=0.75)

#<ss.cons.2binom.prob.q.bothmarg>
accepted.pdiff <- 0.01
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
quantiles <- c(0.25, .75)
z <- ss.cons.2binom.prob.q.bothmarg(quantiles, accepted.pdiff, prior1, prior2, prob=0.7)

#<ss.cons.2binom.avg.q.bothmarg>
accepted.pdiff <- 0.01
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
quantiles <- c(0.25, .75)
z <- ss.cons.2binom.avg.q.bothmarg(quantiles, accepted.pdiff, prior1, prior2)

#<ss.cons.2binom.prob.cdf.bothmarg>
accepted.cdf.diff <- 0.01
cdf.points <- c(0.1, 0.15)
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.prob.cdf.bothmarg(cdf.points, accepted.cdf.diff, prior1, prior2, prob=0.8)

#<ss.cons.2binom.avg.cdf.bothmarg>
accepted.cdf.diff <- 0.01
cdf.points <- c(0.1, 0.15)
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.avg.cdf.bothmarg(cdf.points, accepted.cdf.diff, prior1, prior2)

#<ss.cons.2binom.prob.hpdlimits>
accepted.pdiff <- 0.01
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.prob.hpdlimits(accepted.pdiff, prior1, prior2, prob=0.75)

#<ss.cons.2binom.prob.hpdlimits.mymarg>
accepted.pdiff <- 0.01
clinical.prior <- list(alpha=c(100, 100), beta=c(25, 40))
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.prob.hpdlimits.mymarg(accepted.pdiff, prior1, prior2, clinical.prior, prob=0.7)

#<ss.cons.2binom.worst.hpdlimits>
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
worst.accepted.pdiff <- 0.02
z <- ss.cons.2binom.worst.hpdlimits(worst.accepted.pdiff, prior1, prior2)

#<ss.cons.2binom.avg.cdf>
accepted.cdf.diff <- 0.01
cdf.points <- c(0.1, 0.15)
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.avg.cdf(cdf.points, accepted.cdf.diff, prior1, prior2)

#<ss.cons.2binom.avg.cdf.mymarg>
accepted.cdf.diff <- 0.01
cdf.points <- c(0.1, 0.15)
clinical.prior <- list(alpha=c(100, 100), beta=c(25, 40))
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.avg.cdf.mymarg(cdf.points, accepted.cdf.diff, prior1, prior2, clinical.prior)

#<ss.cons.2binom.prob.cdf>
accepted.cdf.diff <- 0.01
cdf.points <- c(0.1, 0.15)
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.prob.cdf(cdf.points, accepted.cdf.diff, prior1, prior2, prob=0.8)

#<ss.cons.2binom.prob.cdf.mymarg>
accepted.cdf.diff <- 0.01
cdf.points <- c(0.1, 0.15)
clinical.prior <- list(alpha=c(100, 100), beta=c(25, 40))
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.prob.cdf.mymarg(cdf.points, accepted.cdf.diff, prior1, prior2, clinical.prior, prob=0.8)

#<ss.cons.2binom.worst.cdf>
cdf.points <- c(0.1, 0.15)
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
# z <- ss.cons.2binom.worst.cdf(cdf.points, 0.1, prior1, prior2)

#<ss.cons.2binom.avg.q>
accepted.pdiff <- 0.01
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
quantiles <- c(0.25, .75)
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.avg.q(quantiles, accepted.pdiff, prior1, prior2)

#<ss.cons.2binom.avg.q.mymarg>
accepted.pdiff <- 0.01
clinical.prior <- list(alpha=c(100, 100), beta=c(25, 40))
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
quantiles <- c(0.25, .75)
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.avg.q.mymarg(quantiles, accepted.pdiff, prior1, prior2, clinical.prior)

#<ss.cons.2binom.prob.q>
accepted.pdiff <- 0.01
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
quantiles <- c(0.25, .75)
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.prob.q(quantiles, accepted.pdiff, prior1, prior2, prob=0.7)

#<ss.cons.2binom.prob.q.mymarg>
accepted.pdiff <- 0.01
clinical.prior <- list(alpha=c(100, 100), beta=c(25, 40))
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
quantiles <- c(0.25, .75)
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.prob.q.mymarg(quantiles, accepted.pdiff, prior1, prior2, clinical.prior, prob=0.7)

#<ss.cons.2binom.worst.q>
accepted.pdiff <- 0.01
prior1 <- list(alpha=c(194, 200), beta=c(47, 20))
quantiles <- c(0.25, .75)
prior2 <- list(alpha=c(250, 150), beta=c(30, 50))
z <- ss.cons.2binom.worst.q(quantiles, accepted.pdiff, prior1, prior2)