design/devel/TestGPA.R

In Roche/crmPack: Object-Oriented Implementation of CRM Designs

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)
    )
)
plot(data)

model <- DualEndpointEmax(
  mu = c(0, 1),
  Sigma = matrix(c(1, 0, 0, 1), nrow = 2),
  sigma2W = c(a = 0.1, b = 0.1),
  rho = c(a = 1, b = 1),
  E0 = c(0, 100),
  Emax = c(0, 500),
  ED50 = c(0, 200),
  refDose = 500
)

options <- McmcOptions(
  burnin = 20000,
  step = 3,
  samples = 10000
)
# be sure that mcmc class was loaded (otherwise conflict with coda package)
samples <- mcmc(data, model, options)

print(plot(samples, model, data, extrapolate = FALSE))
print(plot(samples, model, data, extrapolate = TRUE))

nextBest1 <- NextBestDualEndpoint(
  target = c(0.9, 1.0),
  overdose = c(0.35, 1),
  maxOverdoseProb = 0.25
)

nextBest(nextBest = nextBest1, doselimit = 1000, samples, model, data)

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"
)
options <- McmcOptions(
  burnin = 20000,
  step = 3,
  samples = 10000
)
# be sure that mcmc class was loaded (otherwise conflict with coda package)
samples <- mcmc(data, model, options)

nextBest1 <- NextBestDualEndpoint(
  target = c(0.9, 1.0),
  overdose = c(0.35, 1),
  maxOverdoseProb = 0.25
)

nextBest(nextBest = nextBest1, doselimit = 1000, samples, model, data)


# ---------------------------------
# Lets familiarize with the RW1
# ---------------------------------
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)
    )
)

model <- DualEndpointRW(
  mu = c(0, 1),
  Sigma = matrix(c(1, 0, 0, 1), nrow = 2),
  sigma2betaW =
    c(a = 20, b = 50),
  sigma2W =
    c(a = 0.1, b = 0.1),
  rho = 0.0,
  smooth = "RW1"
)

options <- McmcOptions(
  burnin = 20000,
  step = 3,
  samples = 10000
)
emptydata <- DataDual(doseGrid = data@doseGrid)
priorsamples <- mcmc(emptydata, model, options)