ConditionalPower-class {adoptr} | R Documentation |
This score evaluates P[X2 > c2(design, X1) | X1 = x1]. Note that the distribution of X2 is the posterior predictive after observing X1 = x1.
ConditionalPower(dist, prior) Power(dist, prior) ## S4 method for signature 'ConditionalPower,TwoStageDesign' evaluate(s, design, x1, optimization = FALSE, ...)
dist |
a univariate |
prior |
a |
s |
|
design |
object |
x1 |
stage-one test statistic |
optimization |
logical, if |
... |
further optional arguments |
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)