| probUnDes {randomizeR} | R Documentation |
Computing the probability of having desirability scores of zero
Description
Computing the probability of having desirability scores of zero for each desirability function applied to an issue.
Usage
probUnDes(desScore)
## S4 method for signature 'desScores'
probUnDes(desScore)
Arguments
desScore |
an object of the class |
Details
The function probUnDes expects an object that results from the getDesScores
function. For each issue it computes the probability that it achieves an undesirable score,
i.e. a desirability score of 0. In doing so, it weights the zero desirability scores
with the probability that the sequence occurs.
Value
S4 object of class probUnDesirable computing the probability of getting
undesirable scores, i.e. desirability scores of 0.
See Also
Representation of randomization procedures: randPar
Generation of randomization sequences: genSeq
issues for the desirability of randomization sequences
Other desirability topics:
derFunc,
evaluate(),
getDesScores(),
plotDes(),
plotEv()
Examples
# compare Random Allocation Rule to Big Stick Design with respect to different issues
# and their corresponding desirability functions
RAR <- getAllSeq(rarPar(4))
issue1 <- corGuess("CS")
issue2 <- corGuess("DS")
A1 <- assess(RAR, issue1, issue2)
d1 <- derFunc(TV = 0.1, 0.7, 2)
d2 <- derFunc(0.5, c(0.3, 0.8), c(1, 1))
DesScore <- getDesScores(A1, d1, d2, weights = c(5/6, 1/6))
probUnDes(DesScore)