biomLevel | R Documentation |
Compute the biomarker level for a given dose, given model and samples
biomLevel(dose, model, samples, ...) ## S4 method for signature 'numeric,DualEndpoint,Samples' biomLevel(dose, model, samples, xLevel, ...)
dose |
the dose |
model |
the |
samples |
the |
... |
unused |
xLevel |
the grid index of |
biomLevel(dose = numeric, model = DualEndpoint, samples = Samples)
: Here it is very easy, we just return the corresponding
column (index xLevel
) of the biomarker samples matrix, since we save
that in the samples
# Create the data data <- DataDual( x=c(0.1, 0.5, 1.5, 3, 6, 10, 10, 10, 20, 20, 20, 40, 40, 40, 50, 50, 50), y=c(0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1), w=c(0.31, 0.42, 0.59, 0.45, 0.6, 0.7, 0.55, 0.6, 0.52, 0.54, 0.56, 0.43, 0.41, 0.39, 0.34, 0.38, 0.21), doseGrid=c(0.1, 0.5, 1.5, 3, 6, seq(from=10, to=80, by=2))) # Initialize the Dual-Endpoint model (in this case RW1) model <- DualEndpointRW(mu = c(0, 1), Sigma = matrix(c(1, 0, 0, 1), nrow=2), sigma2betaW = 0.01, sigma2W = c(a=0.1, b=0.1), rho = c(a=1, b=1), smooth = "RW1") # Set-up some MCMC parameters and generate samples from the posterior options <- McmcOptions(burnin=100, step=2, samples=500) set.seed(94) samples <- mcmc(data, model, options) # Obtain the biomarker level for a given dose, given model and samples biomLevel(dose = 0.5, model = model, samples = samples, xLevel = 2)
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