Constraints {adoptr} | R Documentation |
Conceptually, constraints work very similar to scores (any score can be put in a constraint). Currently, constraints of the form 'score <=/>= x', 'x <=/>= score' and 'score <=/>= score' are admissable.
## S4 method for signature 'Constraint,TwoStageDesign' evaluate(s, design, optimization = FALSE, ...) ## S4 method for signature 'Constraint' show(object) ## S4 method for signature 'ConditionalScore,numeric' e1 <= e2 ## S4 method for signature 'ConditionalScore,numeric' e1 >= e2 ## S4 method for signature 'numeric,ConditionalScore' e1 <= e2 ## S4 method for signature 'numeric,ConditionalScore' e1 >= e2 ## S4 method for signature 'ConditionalScore,ConditionalScore' e1 <= e2 ## S4 method for signature 'ConditionalScore,ConditionalScore' e1 >= e2 ## S4 method for signature 'UnconditionalScore,numeric' e1 <= e2 ## S4 method for signature 'UnconditionalScore,numeric' e1 >= e2 ## S4 method for signature 'numeric,UnconditionalScore' e1 <= e2 ## S4 method for signature 'numeric,UnconditionalScore' e1 >= e2 ## S4 method for signature 'UnconditionalScore,UnconditionalScore' e1 <= e2 ## S4 method for signature 'UnconditionalScore,UnconditionalScore' e1 >= e2
s |
|
design |
object |
optimization |
logical, if |
... |
further optional arguments |
object |
object to show |
e1 |
left hand side (score or numeric) |
e2 |
right hand side (score or numeric) |
design <- OneStageDesign(50, 1.96) cp <- ConditionalPower(Normal(), PointMassPrior(0.4, 1)) pow <- Power(Normal(), PointMassPrior(0.4, 1)) # unconditional power constraint constraint1 <- pow >= 0.8 evaluate(constraint1, design) # conditional power constraint constraint2 <- cp >= 0.7 evaluate(constraint2, design, .5) constraint3 <- 0.7 <= cp # same as constraint2 evaluate(constraint3, design, .5)