Usage
n.opt(nu = 0, tau = 1, sigma = 1, alpha = 0.025,
gain.constant = 1, gain.function = function(X, mu) 0,
fixed.cost = 0, sample.cost = 0.005,
k = 1, n.min = 1, n.max = 50, n.step = 1,
n.iter = 10000, n.burn.in = 1000, n.adapt = 1000,
regression.type = "loess",
plot.results = TRUE, independent.SE = FALSE,
parallel = FALSE, path.to.package = NA)
Arguments
nu
The mean of the conjugate normal prior distribution for the unknown
population mean.
tau
The standard deviation of the conjugate normal prior distribution for the unknown
population mean.
sigma
The known population standard deviation for each individual response in the trial.
alpha
The significance level in the one-sided test used by the regulatory
authority to decide upon marketing approval for the new treatment.
gain.constant
A constant utility gain received upon treatment approval. The total
gain consists of the sum of gain.constant and gain.function.
gain.function
A variable utility gain obtained in addition to the constant utility
gain upon treatment approval.
fixed.cost
The fixed cost of performing the trial.
sample.cost
The marginal cost per observation for the trial.
k
The number independent, parallel trials. Must be an integer greater
than zero.
n.min
Lower limit for the one-dimensional grid for the sample size.
n.max
Upper limit for the one-dimensional grid for the sample size.
n.step
The step size of the grid for the sample size.
n.iter
The number of iterations in the JAGS MCMC simulation.
n.burn.in
The number of burn iterations prior to the JAGS MCMC simulation.
n.adapt
The number of adaptation iterations prior to the burn in and JAGS MCMC simulation.
regression.type
If set to "loess", the default value, then local polynomial
regression will be used (via a call to fit.loess) to fit the grid
simulation results. If set to "gpr", GPR regression will be
used instead. For any other value, no regression is performed and
the optimisation done will consist of a maximisation over the values
corresponding to the grid points.
plot.results
Set to TRUE if a plot of the results of the simulation over
the grid is to be constructed.
independent.SE
If TRUE, then the standard errors of the sample means used to estimate the expected
utility will be computed under the assumption of i.i.d. sampling. If
FALSE, the standard errors are instead computed using the
coda::spectrum0.ar function.
parallel
Set to TRUE if the simulations over the grid should be done in
parallel on a multi-core processor. The default value FALSE
leads to single-core computations.
path.to.package
The search path to the installation directory of bdpopt. For the
default value, the function will attempt to find the path using search.