# NOT RUN {
# making a gsDesign object first may be easiest...
x <- gsDesign()
# take a look at it
x
# default plot for gsDesign object shows boundaries
plot(x)
# plottype=2 shows boundary crossing probabilities
plot(x, plottype=2)
# now add boundary crossing probabilities and
# expected sample size for more theta values
y <- gsProbability(d=x, theta=x$delta*seq(0, 2, .25))
class(y)
# note that "y" below is equivalent to print(y) and
# print.gsProbability(y)
y
# the plot does not change from before since this is a
# gsDesign object; note that theta/delta is on x axis
plot(y, plottype=2)
# now let's see what happens with a gsProbability object
z <- gsProbability(k=3, a=x$lower$bound, b=x$upper$bound,
n.I=x$n.I, theta=x$delta*seq(0, 2, .25))
# with the above form, the results is a gsProbability object
class(z)
z
# default plottype is now 2
# this is the same range for theta, but plot now has theta on x axis
plot(z)
# }
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