ConditionalPower-class {adoptr} | R Documentation |
(Conditional) Power of a Design
Description
This score evaluates P[X2 > c2(design, X1) | X1 = x1]. Note that the distribution of X2 is the posterior predictive after observing X1 = x1.
Usage
ConditionalPower(dist, prior, label = "Pr[x2>=c2(x1)|x1]")
Power(dist, prior, label = "Pr[x2>=c2(x1)]")
## S4 method for signature 'ConditionalPower,TwoStageDesign'
evaluate(s, design, x1, optimization = FALSE, ...)
Arguments
dist |
a univariate |
prior |
a |
label |
object label (string) |
s |
|
design |
object |
x1 |
stage-one test statistic |
optimization |
logical, if |
... |
further optional arguments |
See Also
Examples
prior <- PointMassPrior(.4, 1)
cp <- ConditionalPower(Normal(), prior)
evaluate(
cp,
TwoStageDesign(50, .0, 2.0, 50, 2.0, order = 5L),
x1 = 1
)
# these two are equivalent:
expected(cp, Normal(), prior)
Power(Normal(), prior)
[Package adoptr version 1.0.1 Index]