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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