DataMixture-class | R Documentation |
Class for the data with mixture sharing
xshare
the doses for the share patients
yshare
the vector of toxicity events (0 or 1 integers) for the share patients
nObsshare
number of share patients
LogisticLogNormalMixture
for the explanation
how to use this data class
## decide on the dose grid:
doseGrid <- 1:80
## and MCMC options:
options <- McmcOptions()
## the classic model would be:
model <- LogisticLogNormal(mean = c(-0.85, 1),
cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
refDose = 50)
nodata <- Data(doseGrid=doseGrid)
priorSamples <- mcmc(nodata, model, options)
plot(priorSamples, model, nodata)
## set up the mixture model and data share object:
modelShare <- LogisticLogNormalMixture(shareWeight=0.1,
mean = c(-0.85, 1),
cov = matrix(c(1, -0.5, -0.5, 1), nrow = 2),
refDose = 50)
nodataShare <- DataMixture(doseGrid=doseGrid,
xshare=
c(rep(10, 4),
rep(20, 4),
rep(40, 4)),
yshare=
c(rep(0L, 4),
rep(0L, 4),
rep(0L, 4)))
## now compare with the resulting prior model:
priorSamplesShare <- mcmc(nodataShare, modelShare, options)
plot(priorSamplesShare, modelShare, nodataShare)
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